Q2 2026 CXApp Inc Earnings Call and Investor Forum

August 13, 2026

Speaker #1: Good afternoon, everyone, and thank you for joining us for our Q2 earnings call investor forum. I want to bring one topic today: Q2 fundamentally changed the trajectory of SKY.

Speaker #1: For the last several years, we have been building and improving our technology inside some of the world's most demanding enterprises. We built trust, we built proprietary workplace intelligence, and we built the foundation of agentic AI platforms.

Speaker #1: Now we're entering this scaling phase, and this is where I wanted to also tell you as investors the 3 things I want to take out of today's meeting.

Speaker #1: Number 1: engine room transforms our scale and gives us something strategically critical: mid-market distribution. Secondly: SKY 2.0 has moved from strategy into production. And third: we now see a much clearer operating model for translating growth into operating leverage and ultimately profitable growth.

Speaker #1: To do that, I've already extensive agenda for today, I'm excited to have our leadership team join us, and I'm Param Sheikh, I'm the chairman and CEO of CXAI, and with me today I'll have Chris Wiegand, who's our general manager of North America, talking about our enterprise business and the scale we're getting there.

Speaker #1: Our newest leader, Adam Laurie, who's the general manager of Australia, previously the managing director of engine room, will be with us as well. And my new partner, Melissa Prisni, who's stepped up to be the interim CFO after the transaction.

Speaker #1: She was leading the finance function at engine room, so Melissa, welcome. And last but not least, we'll have an industry expert guest, Zoe Chen, Zoe's very well-respected in the industry, and we'd love to hear her views on the human experience and AI.

Speaker #1: So with that, let me show you the agenda for today. We're going to first have the Q2 earnings call. Melissa and I will take that, and we'll run you through the financials, we'll run you through what were the wins, what happened this quarter, what is our outlook for the quarter and for the future.

Speaker #1: Then we'll adjourn around 5:30, we'll take an intermission, we won't actually adjourn, but we'll just take a little break. If we end early, or we'll transition directly into our investor forum.

Speaker #1: And the investor forum will really focus on, number 1, from my perspective, the vision and what do I think about SKY 2.0 and the agentic enterprise, what's the market, what's the opportunity, where we're at, and where we're going.

Speaker #1: Then I'm going to hand over to Chris to talk about North America, the customers and products, and growth, and then go more detail on the product side there.

Speaker #1: And then Adam will talk about the Australasian opportunity that he sees, the mid-market scale, what he's been winning, and continues to win, as we speak this quarter, and what his future path is.

Speaker #1: And then we'll round up with Fireside Chat with Zoe, which I'm hopefully you're going to enjoy her perspective, and we'll close. So it's going to be a packed agenda.

Speaker #1: I know a lot of you have been sending some questions, we'll take some questions. In the Q&A section as well. So I appreciate that.

Speaker #1: So with that, let's get going with the business. So let's talk about our Q2 earnings. And as I said earlier, the 3 themes. Number 1: engine room is transformative.

Speaker #1: Number 2: SKY 2.0 is real, is available. And third: we're now seeing a clear operating model for translating growth into operating leverage and ultimately profitable growth.

Speaker #1: And we at SKY are building the agentic AI operating layer. So before we go into the business numbers, let me talk to you guys about the just make sure you have the disclaimer slide on what is, you know, what are the forward-looking statements, make sure you read that.

Speaker #1: They're Safe Harbor. Please review the Safe Harbor non-GAAP disclosures in today's presentation and our SEC filings for the applicable risk assumptions and reconciliations. We will be filing the 10Q tomorrow, and so you can read that when you get that.

Speaker #1: So let me talk about, you know, the company we have today, right? And the company we have today is pretty amazing. You know, we are deployed globally around 200-plus cities with more than 60-plus customers now, supporting a large install base of users.

Speaker #1: We operate inside demanding enterprise environments where security, privacy, reliability integration are not optional. They're necessary. This matters because our AI strategy starts from something valuable: enterprise trust and real operating context.

Speaker #1: Context is very important. We aren't beginning by building an AI application and trying to figure out where it fits. We already operate inside the enterprise.

Speaker #1: We understand people, places, workflows in enterprise systems. And SKY 2.0 is about making that context increasingly intelligent and actionable. So we're headquartered in San Francisco, Bay Area.

Speaker #1: As you know, we have teams in Toronto, in Manila, and now we're excited to welcome the Australian team, which is headquartered out of Melbourne, but they're all across Australia as well in New Zealand.

Speaker #1: We're excited to have them on board. And this gives us the global coverage, you know, we have around 70 team members now globally, and they're all working hard and making AI successful in the enterprise market that we're in.

Speaker #1: So before we get to the numbers, let me just give you context of where we're being and where we're going, right? So SKY 1.0 established the enterprise foundation.

Speaker #1: It showed us that we have great software, workplace software that has people and place intelligence. We have Fortune 500 customers. They have high trust, high complexity deployments.

Speaker #1: This remains an important part of business. We've made some significant strides in the last 2 quarters. You know, Chris is going to talk about those customer case studies and stuff, but it's been amazing there.

Speaker #1: You know, we have around 70 team members now globally, and they're all working hard, making AI successful in the enterprise market that we're in.

Speaker #1: But SKY 2.0 really expands that opportunity. We're moving primarily from understanding places which is really the flow product, which is where and how people work, to person, which is what we're calling BEAT.

Speaker #1: So, before we get to the numbers, let me just give you context of where we've been and where we're going, right? So, Sky 1.0 established the enterprise foundation. It showed us that we have— you know, great software, workplace software that has people and place intelligence. We have Fortune 500 customers, and we have high-trust, high-complexity deployments.

Speaker #1: What an individual and team need to accomplish and what should happen next, in your life as a worker. And now we're moving with engine room into business.

Speaker #1: How companies acquire customers, convert demand, and grow. That business context is significantly strengthened by engine room, as you know. And at any of those experiences is the same SKY agentic platform.

Speaker #1: This remains an important part of business. We've made some significant strides in the last two quarters. You know, Chris is going to talk about those customer case studies and stuff, but it's been amazing there.

Speaker #1: The strategy from here is very straightforward, proven enterprise technology, mid-market distribution, prioritized AI, and scaled recurring revenue. We're going to run that flywheel cycle because we've got now an agentic platform that we can leverage across multiple verticals, and more importantly, we now have a new distribution mechanism through engine room.

Speaker #1: But Sky 2.0 really expands that opportunity. We're moving primarily from understanding places—which is really the Flow product, which is where and how people work—to person, which is what we're calling BEAT: what an individual and team need to accomplish, and what should happen next in your life as a worker.

Speaker #1: So this is the transformation I'm talking about. This is what we're executing on, and we're super excited about this opportunity. So let me go into the business for this quarter.

Speaker #1: And now we're moving with Engine Room into business—how companies acquire customers, convert demand, and grow. That business context is significantly strengthened by Engine Room, as you know.

Speaker #1: And what happened this quarter. So this is a pretty exciting time for CXCI or SKY. As you can see on sorry, as you can see on our highlights for the quarter, the 6 main highlights.

Speaker #1: And underneath those experiences is the same Sky Agenda platform. The strategy from here is very straightforward: proven enterprise technology, mid-market distribution, prioritized AI, and scaled recurring revenue.

Speaker #1: But the biggest one is the engine room transaction. It is transformative. I'm going to talk more about it in detail. But it really did change the revenue trajectory for the company.

Speaker #1: We're going to run that flywheel cycle because we've got, now, an agentic platform that we can leverage across multiple verticals. More importantly, we now have a new distribution mechanism through Engine Room.

Speaker #1: And more importantly, quarter over quarter increase of probably 79% revenue growth from 950,000 in Q1 to approximately 1.7 million in Q2. The more important thing is what sits underneath that growth.

Speaker #1: So this is the transformation I'm talking about. This is what we're executing on, and we're super excited about this opportunity. So let me go into the business for this quarter.

Speaker #1: Enterprise retention remains strong. Two major Fortune 500 customers renewed their relationship with SKY. In enterprise software, renewals matter enormously because they validate the product after the initial sale.

Speaker #1: And what happened this quarter—so this is a pretty exciting time for CXAI, or Sky, as you can see—sorry, as you can see on our highlights for the quarter, the six main highlights.

Speaker #1: Customers are continuing to choose SKY. We also added a significant new win in the financial services sector. This is a 3-year multi-million dollar recurring revenue deal.

Speaker #1: But the biggest one is the engine room transaction. It is transformative. I'm going to talk more about it in detail, but it really did change the revenue trajectory for the company.

Speaker #1: It went through a very competitive RFP. We're super excited to have that customer on board. And they're scaling with us. They're beginning this quarter.

Speaker #1: And more importantly, quarter-over-quarter, an increase of probably 79% revenue growth from $950,000 in Q1 to approximately $1.7 million in Q2. The more important thing is what sits underneath that growth.

Speaker #1: And it's a really important win for the team. And it's important for two reasons. First, it demonstrates continued demand from highly sophisticated regulated customers.

Speaker #1: Enterprise retention remains strong. Two major Fortune 500 customers renewed their relationship with Sky. In enterprise software, renewals matter enormously because they validate the product after the initial sale.

Speaker #1: Secondly, these are the types of customers where SKY 2.0 can expand over time across additional modules users and AI capabilities. The other big achievement for this quarter is we moved SKY 2.0 into deployment.

Speaker #1: Customers that continue to choose Sky— we also added a significant new win in the financial services sector. This is a three-year, multi-million dollar recurring revenue deal.

Speaker #1: And that's a big win for us. And the progression is when deploy adopt expand exactly what we want to replicate. And with 2.0, really, what we get is an agentic AI platform that allows the user to navigate their workplace, navigate their work, and navigate their experiences across the whole enterprise.

Speaker #1: It went through a very competitive RFP. We're super excited to have that customer on board, and they're scaling with us. They're beginning this quarter.

Speaker #1: And it's a really important win for the team, and it's important for two reasons. First, it demonstrates continued demand from highly sophisticated, regulated customers.

Speaker #1: And that's very exciting. And our customers, the reason why they're selecting us is because we have SKY 2.0. That's the wins we got. That's the renewals we got are all because of SKY 2.0.

Speaker #1: Secondly, these are the types of customers where Sky 2.0 can expand over time across additional modules, users, and AI capabilities. The other big achievement for this quarter is we moved Sky 2.0 into deployment.

Speaker #1: And as you know, during the quarter, we completed the engine room transaction. So for Q2, we only have one month because it was the month of June.

Speaker #1: And that's a big win for us. The progression is when we deploy, adopt, expand—exactly what we want to replicate. And with 2.0, really, what we get is an agentic AI platform that allows the user to, you know, navigate their workplace, navigate their work, and navigate their experiences across the whole enterprise.

Speaker #1: That engine room is part of the revenue. And it's been an amazing one month because they've continued to get new clients. They've got double digit growth.

Speaker #1: They're going through this annuals process where they've got commitments from existing clients. So it's been really good. And so all of these 6 factors combined really have been super successful for the company.

Speaker #1: And that's very exciting. And our customers— the reason why they're selecting us is because we have Sky 2.0. That's the wins we got, that's the renewals we got, are all because of Sky 2.0.

Speaker #1: I want to congratulate the team on the job well done. And it builds the momentum. It strengthens the foundation for SKY 2.0 and our scaled growth moving forward.

Speaker #1: And as you know, during the quarter, we completed the Engine Room transaction. So for Q2, we only have one month—because it was the month of June—that Engine Room is part of the revenue.

Speaker #1: So let me tell you, you know, a little bit about engine room. And what better than just to roll a video? So operator, if you can roll the video.

Speaker #1: And it's been an amazing one month because they've continued to get new clients, they've got double-digit growth, and they're going through this annuals process where they've got commitments from existing clients.

Speaker #1: So it's been really good, and all of these six factors combined have really been super successful for the company. I want to congratulate the team on a job well done.

Speaker #1: And it builds the momentum. It strengthens the foundation for Sky 2.0 and our scaled growth moving forward. So let me tell you a little bit about Engine Room, and what better than just to roll a video.

Speaker #1: So, operator, if you can roll the video. All right, cool. That's pretty exciting. So, when I talk about Engine Room, I talk about it as being transformative.

Speaker #1: All right, cool. That's pretty exciting. So when I talk about engine room, I talk about it as being transformative. And as you can see from the video, it's pretty exciting stuff to do.

Speaker #1: And they've been at it for 13 years. And they've made amazing progress in getting clients and making sure that they have really solid footing.

Speaker #1: So let me tell you why this is transformative. Engine room does not simply add revenue. It changes the starting point for SKY. Engine room brings more than 8 million of revenue approximately 1.6 million adjusted EBITDA a highly recurring revenue profile.

Speaker #1: Customer relationships. For strategically, three things matter even more for me. Number one, distribution. SKY historically sold into large enterprises through an enterprise sales process.

Speaker #1: And as you can see from the video, it's pretty exciting stuff they do, and they've been at it for 13 years. They've made amazing progress in getting clients and making sure that they have really solid footing.

Speaker #1: Engine room gives us structured relationship with dozens of mid-market businesses. That gives us a much faster proving ground and future distribution channel for SKY AI products.

Speaker #1: So let me tell you why this is transformative. Engine Room does not simply add revenue; it changes the starting point for Sky. Engine Room brings more than $8 million of revenue, approximately $1.6 million of adjusted EBITDA, a highly recurring revenue profile, and more than 50 mid-market customer relationships.

Speaker #1: Number two, business context. As I said earlier, SKY already understands workplace and employee context. And that's one of our moats in differentiation. Engine room brings customer acquisition, performance, marketing, and growth data.

Speaker #1: That allows SKY 2.0 to expand from understanding how people work to understanding how businesses grow. Number three, cross-sell. We can introduce SKY capabilities into engine room's customer base.

Speaker #1: But strategically, three things matter even more for me. Number one, distribution. Sky historically sold into large enterprises through an enterprise sales process. Engine Room gives us trusted relationships with dozens of mid-market businesses.

Speaker #1: And we can introduce engine room's growth capabilities into SKY's enterprise products. So the combined company has an enterprise anchor, a mid-market growth engine, and a shared agentic AI platform.

Speaker #1: That gives us a much faster proving ground and future distribution chance for Sky AI products. Number two, business context. As I said earlier, Sky already understands workplace and employee context, and that's one of our moats and differentiation.

Speaker #1: And the combination moves SKY to more than 12 million of analyzed revenue scale. This acquisition created scale. Our job now is to turn that scale into operating leverage.

Speaker #1: Engine Room brings customer acquisition, performance, marketing, and growth data. That allows Sky 2.0 to expand from understanding how people work to understanding how businesses grow.

Speaker #1: So I'm super excited about this. I think this is the right move for the company. It positions us ready for the growth engine. And that we've been talking about, the double digit growth, it gives us that flexibility in terms of having the ability to innovate in a very interesting market, Australia, I'll talk more about that in the next we'll go more deeper into it.

Speaker #1: Number three, cross-sell. We can introduce Sky’s capabilities into Engine Room’s customer base, and we can introduce Engine Room’s growth capabilities into Sky’s enterprise products.

Speaker #1: So, the combined company has an enterprise anchor, a mid-market growth engine, and a shared agentic AI platform. And the combination moves Sky to more than $12 million of analyzed revenue scale.

Speaker #1: But I just want to share this story with you and share with you that this has been an amazing, amazing transaction for us. So with that, I want to move on to the financials for Q2.

Speaker #1: This acquisition created scale. Our job now is to turn that scale into operating leverage. So I'm super excited about this. I think this is the right move for the company.

Speaker #1: You know, I'm going to turn it over to Melissa to walk through the quarter in more detail. As you listen to the financial results, I would focus on one important relationship.

Speaker #1: It positions us, ready for the growth engine that we've been talking about—the double-digit growth. It gives us that flexibility in terms of having the ability to innovate in a very interesting market, Australia. I'll talk more about that in the investor forum.

Speaker #1: How rapidly the revenue base is changing relative to the cost structure. Melissa, all yours.

Speaker #2: Thanks, Cram. So the quarter over quarter comparisons demonstrate that steps change is taking place in the business. Between Q1 and Q2, revenue has increased approximately 950,000 dollars.

Speaker #1: We will go deeper into it, but I just want to share this story with you, and share with you that this has been an amazing, amazing transaction for us.

Speaker #1: So with that, I want to move on to the financials for Q2. I'm going to turn it over to Melissa to walk through the quarter in more detail.

Speaker #2: In Q1 to 1.7 million dollars in Q2, representing as Cram previously mentioned, a 79% sequential growth. Our annual recurring revenue has increased from 3.6 million dollars to 11.5 million dollars.

Speaker #1: As you listen to the financial results, I would focus on one important relationship: how rapidly the revenue base is changing relative to the cost structure.

Speaker #1: Melissa, all yours.

Speaker #2: Thanks, Khurram. So, the quarter-over-quarter comparisons demonstrate that a step change is taking place in the business. Between Q1 and Q2, revenue has increased approximately $950,000.

Speaker #2: One second. We've jumped. Let me just find that slide again. Sorry about that. Net revenue retention has increased from approximately 98% to 99.3, continuing to demonstrate our strong retention across installed bases.

Speaker #2: In Q1 to $1.7 million in Q2, representing, as Khurram previously mentioned, a 79% sequential growth. Our annual recurring revenue has increased from $3.6 million to $11.5 million.

Speaker #2: Total assets increased from approximately 33 million to 36 million. And our cash EBITDA improved from approximately negative 3 million in quarter one to negative 2.68 million in quarter two.

Speaker #2: One second—we've jumped. Let me just find that slide again. Sorry about that. Net revenue retention has increased from approximately 98% to 99.3%, continuing to demonstrate our strong retention across installed bases.

Speaker #2: EPS was approximately negative 0.10 compared with negative 0.09 in Q1. So the key takeaway quarter over quarter is that revenue base increased substantially while cash EBITDA improved modestly.

Speaker #2: We're still investing in integration and development of the combined businesses, but the operating model is beginning to show greater scale. The year-over-year comparison shows the main progress.

Speaker #2: Total assets increased from approximately $33 million to $36 million. And our cash EBITDA improved from approximately negative $3 million in Q1 to negative $2.68 million in Q2.

Speaker #2: Revenue increased approximately 42% from 1.2 million dollars in Q2 of 2025 to 1.7 million this quarter. ARR increases from 4.5 million to, again, the 11.5 million, an increase of approximately 156%.

Speaker #2: EPS was approximately negative $0.10, compared with negative $0.09 in Q1. So the key takeaway quarter-over-quarter is that the revenue base increased substantially, while cash EBITDA improved modestly.

Speaker #2: Net revenue retention increased by more than 5% to approximately 99.3. Assets also increased 22% from 29.6 million to approximately 36 million. Cash EBITDA was approximately negative 2.7 million, which is a neutral position compared to a year ago.

Speaker #2: And EPS has improved from approximately negative 0.16 to negative 0.10 between the two years. The most significant change in the financial profile is therefore the scale of the recurring revenue base.

Speaker #2: Revenue increased approximately 42%, from $1.2 million in Q2 of 2025 to $1.7 million this quarter. ARR increases from $4.5 million to, again, $11.5 million, an increase of approximately 156%.

Speaker #2: While we continue to manage investments, required to support integration and future growth. And now let me put this cost structure into perspective. Total operating expenses increased 275,000 dollars quarter over quarter, or 5.6%.

Speaker #2: Net revenue retention increased by more than 5% to approximately 99.3%. Assets also increased 22%, from $29.6 million to approximately $36 million. Cash EBITDA was approximately negative $2.7 million, which is a neutral position compared to a year ago.

Speaker #2: However, we do need to compare that with the approximately 79% sequential revenue growth. The increase in operating costs was driven primarily by the engine room acquisition and associated operating activity.

Speaker #2: And EPS has improved from approximately negative $0.16 to negative $0.10 between the two years. The most significant change in the financial profile is therefore the scale of the recurring revenue base.

Speaker #2: Importantly, these Q2 numbers do not yet reflect the benefit of the operating synergies we are implementing as we integrate the businesses. Our focus moving forward is straightforward.

Speaker #2: While we continue to manage investments required to support integration and future growth. And now, let me put this cost structure into perspective. Total operating expenses increased approximately $275,000 quarter-over-quarter, or 5.6%.

Speaker #2: Grow revenue faster than expenses. We expect to accomplish that through shared functions, tighter operating discipline, productized implementation, increasing automation, and a higher recurring software contribution.

Speaker #2: However, we do need to compare that with the approximately 79% sequential revenue growth. The increase in operating costs was driven primarily by the Engine Room acquisition and associated operating activity.

Speaker #2: That operating leverage is central to the financial strategy for the combined company. And I'll turn it back to Cram now.

Speaker #1: Cram, you're muted.

Speaker #3: Thank you, Melissa. I apologize. I was on mute. This was a really great quarter, as you can see. We are finally showing the value of our technology platform, but also the engine room acquisition.

Speaker #2: We expect to accomplish that through shared functions, tighter operating discipline, productized implementation, increasing automation, and a higher recurring software contribution. That operating leverage is central to the financial strategy for the combined company.

Speaker #3: But I want to put in perspective what I see the value of this company as we move forward. And this is the valuation is based on numbers that we get from KeyBank, which doesn't monthly survey on software benchmarks and looks at all the recurring revenue-based businesses and software businesses.

Speaker #2: And I'll turn it back to Khurram now.

Speaker #3: So as I think of our business now, it is an AI-powered software business that is at much larger scale. And the scale is, you know, last quarter we were a million a quarter.

Speaker #1: Khurram, you're muted.

Speaker #3: Thank you, Melissa. I apologize—I was on mute. This was a really great quarter, as you can see. We are finally showing the value of our technology platform, but also the Engine Room acquisition.

Speaker #3: This quarter we are now 1.7 million a quarter. And with the full engine room integration, we'll be hitting 3 million a quarter or 12 million analyzed by next quarter.

Speaker #3: And that shows real growth as well as shows real momentum. And scale. And based on that, when you think about that business and you think about that software business with the metrics we have, you know, just on a conservative basis, we're it's a 9.7x multiple, right?

Speaker #3: But I want to put in perspective what I see as the value of this company as we move forward. And this valuation is based on numbers that we get from KeyBank, which does a monthly survey on software benchmarks and looks at all the recurring revenue-based businesses and software businesses.

Speaker #3: So as I think of our business now, it is an AI-powered software business that is at a much larger scale. And the scale is, you know, last quarter we were at $1 million a quarter.

Speaker #3: That's more on next 12 months revenue. I'm just saying that revenue we have now, we will have now by Q3. So to me, we're at a very attractive stock price right now, given where we're at in terms of the valuation that we should command.

Speaker #3: This quarter, we are now at $1.7 million per quarter. And with the full engine room integration, we'll be hitting $3 million a quarter, or $12 million annualized, by next quarter.

Speaker #3: I do believe that we will continue to perform. And given our double-digit growth strategy, we believe by, you know, second half of 2027, we will be growing and getting to the break-even point.

Speaker #3: And that shows real growth, as well as real momentum and scale. And based on that, when you think about that business and you think about that software business, with the metrics we have, you know, just on a conservative basis, it's a 9.7x multiple, right?

Speaker #3: And that's where our focus is. Our focus is really to get to that level. And you can see the metrics based on that. This is all illustrated, by the way.

Speaker #3: This is not a valuation guidance. I'm just taking industry benchmarks and showing you what the value of this company is and the fact that we've now built that agenda together.

Speaker #3: That's more on next 12 months' revenue. I'm just saying that the revenue we have now, we will have by Q3. So to me, we're at a very attractive stock price right now, given where we're at in terms of the valuation that we should command.

Speaker #3: And now it's about growth and distribution. And this is where we did the engine room transaction. And this is where we feel very strongly about the growth and scale of the business.

Speaker #3: I do believe that we will continue to perform. And given our double-digit growth strategy, we believe that by the second half of 2027, we will be growing and getting to the break-even point.

Speaker #3: You know, can we sustain this growth? Can we increase software mix? Can we transfer into greater revenue scale? Absolutely. And that's where the two businesses have been complementary, but we're going to help each other scale up faster.

Speaker #3: And that's where our focus is. Our focus is really to get to that level, and you can see the metrics based on that. This is all illustrated, by the way.

Speaker #3: Now, let me talk about probably the most important one of the most important charts in the slide deck here. It's about the path to break-even, right?

Speaker #3: This is not a valuation guidance. I'm just taking industry benchmarks and showing you what the value of this company is and the fact that we've now built that agentic AI platform, that R&D expense has been done, and now it's about growth and distribution.

Speaker #3: And again, this is a directional operating framework, not specific financial guidance. The engine room acquisition gives us a combined revenue of more than 12 million dollars.

Speaker #3: And this is where we did the engine room transaction, and this is where we feel very strongly about the growth and scale of the business.

Speaker #3: From here, there are several identifiable levers. First, organic growth. Continue expanding the sky enterprise business and engine rooms customer base. That's obvious. Second is cross-sell.

Speaker #3: Introduce additional sky modules into existing enterprise customers. Chris is going to talk a lot about that today. Number two is introduce sky agenda AI products into the engine rooms mid-market customer relationship.

Speaker #3: Now, let me talk about probably the most important—one of the most important—charts in the slide deck here. It's about the path to break-even, right?

Speaker #3: That's the second cross-sell that we think is very important. Thirdly, increase software monetization. You'll talk about flow. We'll talk about analytics, events, and our emerging personal execution capabilities called BEAT.

Speaker #3: And again, this is a directional operating framework, not specific financial guidance. The Engine Room acquisition gives us a combined revenue of more than $12 million.

Speaker #3: All increase our opportunity to generate recurring software revenue from the same platform. And fourth, prioritize that mid-market motion. For mid-market customers, we don't want to recreate a long enterprise implementation.

Speaker #3: From here, there are several identifiable levers. First, organic growth—continue expanding the Sky Enterprise business and Engine Rooms customer base. That's obvious. Second is cross-sell.

Speaker #3: Our objective is to standardize the products, standardize the connectors, faster provisioning, and lower cost to serve. And fifth, operating leverage. We now have opportunities to share infrastructure, technology, corporate functions, and delivery capabilities across a much larger revenue base.

Speaker #3: Introduce additional Sky modules into existing enterprise customers. Chris is going to talk a lot about that today. Number two is to introduce Sky agentic AI products into the engine rooms mid-market customer relationship.

Speaker #3: That's the second cross-sell that we think is very important. Thirdly, increase software monetization. We'll talk about Flow, we'll talk about Analytics, Events, and our emerging personal execution capabilities called BEAT.

Speaker #3: That's the synergy that Melissa talked about. The operating model we are working towards is characterized by, number one, double-digit revenue growth, which is part of our strategy as well as what engine room is already on.

Speaker #3: Number two, recurring revenue more than 95%. Gross margin above 70%. Software mix above 95%. Increasing revenue per customer. We're already at 150 to 200,000 per client per year, which is really great.

Speaker #3: Our objective is to standardize the products, standardize the connectors, provide faster provisioning, and lower cost to serve. Now, fifth, operating leverage. We now have opportunities to share infrastructure, technology, corporate functions, and delivery capabilities across a much larger revenue base.

Speaker #3: And the discipline expense growth, which now we can do with the larger scale. If we execute against those levers, we believe there's a credible path towards break-even in the second half of 2027, followed by profitable growth.

Speaker #3: So I want to now close with why sky. Why do you want to continue to invest and be part of this journey? Why is this moment different for sky?

Speaker #3: Reason number one, engine room is transformative. It immediately increases our revenue scale. It gives us profitable operating capability and perhaps more importantly, it gives sky a mid-market distribution engine that we did not previously have.

Speaker #3: And the disciplined expense growth, which now we can do with the larger scale. If we execute against those levers, we believe there's a credible path towards break-even in the second half of 2027, followed by profitable growth.

Speaker #3: Reason number two, sky 2.0 is now in production. This is no longer simply a roadmap or an AI narrative. We are ready now to deploy this across our clients.

Speaker #3: So I want to now close with: why Sky? Why do you want to continue to invest and be part of this journey? Why is this moment different for Sky?

Speaker #3: We can successful in the demonstrations and prototypes and getting it through our clients. They're going through a lot of validation, but now it is launching.

Speaker #3: It is launching live with a new client. It's also launching live with existing clients. And now we have these new enterprise logos signing multi-year agreements.

Speaker #3: Reason number one: Engine Room is transformative. It immediately increases our revenue scale, gives us profitable operating capability, and perhaps more importantly, gives Sky a mid-market distribution engine that we did not previously have.

Speaker #3: They would not be signing multi-year agreements with us unless they knew that the roadmap and the product we have is going to be long-lasting and for the future.

Speaker #3: And we are expanding the platform from workplace intelligence to personal execution, which is the BEAT, as well as the growth intelligence, which is engine room.

Speaker #3: Reason number two: Sky 2.0 is now in production. This is no longer simply a roadmap or an AI narrative. We are ready now to deploy this across our clients.

Speaker #3: And reason number three, the financial model is becoming more scalable. Q2 revenue increased approximately 79% sequentially, while operating expense increased approximately 5.6%. That does not mean the work is finished.

Speaker #3: We've been successful in the demonstrations and prototypes, and getting it through our clients. They're going through a lot of validation, but now it is launching.

Speaker #3: It is launching live with a new client. It's also launching live with existing clients. And now, we have these new enterprise logos signing multi-year agreements.

Speaker #3: Far from it. But it demonstrates the opportunity for operating leverage as we integrate the businesses' growth, recurring revenue, and prioritize more of what we offer.

Speaker #3: They would not be signing multi-year agreements with us unless they knew that the roadmap and the product we have are going to be long-lasting and built for the future.

Speaker #3: So with that, I'm going to look into some questions that have come in. Let me see. Okay. Question number one, good question. How much cash do you have?

Speaker #3: And we are expanding the platform from workplace intelligence to personal execution, which is the BEAT, as well as the growth intelligence, which is Engine Room.

Speaker #3: And reason number three, the financial model is becoming more scalable. Q2 revenue increased approximately 79% sequentially, while operating expenses increased approximately 5.6%. That does not mean the work is finished.

Speaker #3: What are your liabilities after the purchase of engine room? I'm going to have Melissa take that. Elle?

Speaker #2: Thanks, Crom. So our cash as of 30 June 2026 is 11.7 million dollars. Most importantly, the acquisition costs have been acquisition costs related to engine room have been largely paid.

Speaker #3: Far from it. But it demonstrates the opportunity for operating leverage as we integrate the businesses' growth, recurring revenue, and prioritize more of what we offer.

Speaker #3: So with that, I'm going to look into some questions that have come in. Let me see. Okay, question number one—good question: How much cash do you have?

Speaker #2: And any subsequent funds owing on that on the acquisition of engine room are tied to an earn-out model.

Speaker #3: What are your liabilities after the purchase of the engine room? I'm going to have Melissa take that. Elle?

Speaker #3: No, that's good. So I think just to be clear, the engine room acquisition was 65% cash and the rest was in earn-out. So the team is focused on it.

Speaker #2: Thanks, Khurram. So our cash as of 30 June 2026 is 11.7 million dollars. Most importantly, the acquisition costs have been acquisition costs related to engine room have been largely paid.

Speaker #3: It's a two-year earn-out with growth factors in revenue specifically. So that's going to earn out itself. So we have no other liabilities on engine room except the earn-out.

Speaker #3: And overall, as you can see, the asset base has increased and it has been a very successful integration up to now. Okay. Next question I see is, how quickly should shareholders expect the engine room acquisition to be reflected in sky's report revenue?

Speaker #2: And any subsequent funds owing on that, on the acquisition of Engine Room, are tied to an earn-out model.

Speaker #3: No, that's good. So I think, just to be clear, the Engine Room acquisition was 65% cash and the rest was in earn-out. So the team is focused on it.

Speaker #3: Mel, you want to take that?

Speaker #2: Yeah. So we've actually already captured one month of combined revenues. So that being the month of June. We will be able to demonstrate next quarter.

Speaker #3: It's a two-year earn-out with growth factors in revenue specifically. So that's going to earn out itself, so we have no other liabilities on Engine Room except the earn-out.

Speaker #2: So Q3, the full combined impact over the three months. Of that acquisition and the combined revenue.

Speaker #3: And overall, as you can see, the asset base has increased, and it has been a very successful integration up to now, so. Okay. Next question I see is: How quickly should shareholders expect the Engine Room acquisition to be reflected in Sky's reported revenue?

Speaker #3: Yeah. Okay. I think the next question was one more question. What do you think of the revenue growth over the next 12 months? So look, I gave you some illustrative graph on our potential.

Speaker #3: Mel, do you want to take that?

Speaker #3: As you know, we are focused on double-digit growth. We really believe that the scale we're getting with engine room, the wins we have with our existing enterprise business and new logos coming in that are multi-year, multi-million dollar contract, we're pretty positive on that.

Speaker #2: Yeah. So we've actually already captured one month of combined revenues, that being the month of June. We will be able to demonstrate next quarter, so Q3, the full combined impact over the three months.

Speaker #3: And we're also positive on engine room because they've also increased their they've increased their revenue profiles, the number of clients, and their annuals process has been super successful.

Speaker #2: Of that acquisition, and the combined revenue.

Speaker #3: Yeah, okay. I think the next question was—one more question: what do you think of the revenue growth over the next 12 months? So, look, I gave you some illustrative graph on our potential.

Speaker #3: So anyway, we are pretty positive on that. I think our goal is, like I said, is to have break-even by second half of 2027.

Speaker #3: If we execute our plans that we have and the growth vectors that we're working on, I'm pretty confident in that. And we're also focused on expense management and with agentic AI, we're leveraging AI across our enterprise, all our functions are using AI.

Speaker #3: As you know, we are focused on double-digit growth. We really believe that the scale we're getting with Engine Room, the wins we have with our existing enterprise business, and new logos coming in that are multi-year, multi-million dollar contracts—we're pretty positive on that.

Speaker #3: So we're seeing a lot of efficiency there. As you can see, in terms of our team members, we're very cost-efficient. And so I'm pretty positive that in the next 12 months, we will achieve much higher growth and we will get to the break-even target that we have.

Speaker #3: And we're also positive on Engine Room because they've increased their revenue profiles, the number of clients, and their annuals process has been super successful.

Speaker #3: So, anyway, we are pretty positive on that. I think our goal is, like I said, to have break-even by the second half of 2027.

Speaker #3: Okay. We're running to the end of the call here. So thank you, everybody. I appreciate it. We're going to take a brief pause and we'll join you back in 60 seconds or so for the investor forum.

Speaker #3: If we execute our plans that we have and the growth vectors that we're working on, I'm pretty confident in that. We're also focused on expense management, and with agentic AI, we're leveraging AI across our enterprise. All our functions are using AI.

Speaker #3: Thank you. All right. It's 2:30 p.m. Pacific, 5:30 p.m. Eastern. Welcome to the investor forum. Thank you for people who joined. The earnings call a few minutes ago.

Speaker #3: Okay, we're running to the end of the call here, so thank you, everybody. I appreciate it. We're going to take a brief pause, and we'll join you back in 60 seconds or so for the investor forum.

Speaker #3: Thank you. All right. It's 2:30 p.m. Pacific, 5:30 for the investor forum. Thank you to the people who joined the earnings call a few minutes ago.

Speaker #3: We're going to be more strategic here, more product-focused, really talk to you about the products, the business, the customers, the things underneath the hood that we're working on, and show you the path that we believe is going to be super successful for sky.

Speaker #3: And so I think we share the agenda before. I'm going to start off with the strategic view of the business and more strategically thinking about where we're at, where we're going, and then the team is going to tell you how we're doing what we're doing, what we plan to do next, and then we'll end up with a very interesting fireside chat.

Speaker #3: So thank you for being here and we wish to do this next time live in person, but we're going to do our best to do these demonstrations and these discussions on the webcast.

Speaker #3: We're going to be more strategic here, more product-focused, and really talk to you about the products, the business, the customers, and the things under the hood that we're working on. We'll show you the path that we believe is going to be super successful for Sky.

Speaker #3: So number one, I want to start with something I believe very strongly. And I've been involved in lots of technology transitions. I was involved in the first mobile phone.

Speaker #3: And so, I think we shared the agenda before. I'm going to start off with the strategic view of the business, and more strategically, thinking about where we're at and where we're going. Then the team is going to tell you how we're doing what we're doing, what we plan to do next, and then we'll end up with a very interesting fireside chat.

Speaker #3: I was involved in the first 4G network. I was involved in the first Wi-Fi systems. And then I was involved in 5G and cloud and all this interesting technology developments that have happened.

Speaker #3: And I believe we are at the beginning of another major technology transition in enterprise software. And what I mean by that is, sky started by solving a very real problem.

Speaker #3: Thank you for joining us. We hope to do this live and in person next time, but we'll do our best to present these demonstrations and discussions via the webcast today.

Speaker #3: How people interact with the workplace. And that happened after the pandemic, as you know. COVID kind of created this hybrid environment. What we have built underneath that experience is becoming much bigger than a workplace application.

Speaker #3: So, number one, I want to start with something I believe very strongly. I've been involved in lots of technology transitions. I was involved in the first mobile phone.

Speaker #3: We have enterprise integrations. We have proprietary contacts. We have AI orchestration. We have data. And we have security and trust. And now we're bringing all these assets together into sky2.0, our agentic AI operating layer.

Speaker #3: I was involved in the first 4G networks. I was involved in the first Wi-Fi systems. And then I was involved in 5G and cloud, and all these interesting technology developments that have happened.

Speaker #3: And I believe we are at the beginning of another major technology transition in enterprise software. And what I mean by that is, SKY started by solving a very real problem.

Speaker #3: So our strategy has three priorities. Number one, we position sky around this agentic operating layer. Which I talked about is the context layer. Second, use engine room to give us immediate scale, mid-market distribution, and a much larger customer base.

Speaker #3: How people interact with the workplace changed after the pandemic, as you know. COVID kind of created this hybrid environment. What we have built underneath that experience is becoming much bigger than a workplace application.

Speaker #3: And thirdly, is prioritize what we learn into repeatable vertical AI solutions. This is not simply an evolution of our product I believe it can be an evolution of the company.

Speaker #3: So we're going to talk about that. We're going to go through some real strategic focus on why we're doing this. So let me explain why the timing is important in the industry right now.

Speaker #3: So our strategy has three priorities. Number one, we position Sky around this agentic operating layer, which I talked about as a context layer. Second, use Engine Room to give us immediate scale, mid-market distribution, and a much larger customer base.

Speaker #3: Enterprise software is evolving, as we speak. The first generation of enterprise software created systems of record. Then SaaS and analytics gave us applications, dashboards, and visibility.

Speaker #3: But visibility is no longer enough. The next generation of enterprise software is about action, about getting stuff done, basically. AI agents will increasingly understand context, make recommendations, coordinate workflows, and actually complete outcomes.

Speaker #3: And thirdly, it's to prioritize what we learn into repeatable vertical AI solutions. This is not simply an evolution of our product. I believe it can be an evolution of the company.

Speaker #3: And that is the layer I want sky to own. Not another chatbot, not another dashboard, not another AI feature added onto an application. The operating layer between the enterprise systems is data, it's people, and the actions that need to happen next.

Speaker #3: Employees want fewer applications. Executives want decisions rather than more dashboards. And mid-market businesses want practical AI that produces value today. Without having to assemble teams of AI engineers to build it themselves.

Speaker #3: But visibility is no longer enough. The next generation of enterprise software is about action—about getting stuff done, basically. AI agents will increasingly understand context, make recommendations, coordinate workflows, and actually complete outcomes.

Speaker #3: This is the opportunity that we are designing sky around. So we're building the agentic AI layer for enterprises to work and grow, and that is our focus.

Speaker #3: And that is the layer I want Sky to own—not another chatbot, not another dashboard, not another AI feature added onto an application. The operating layer between the enterprise systems, its data, its people, and the actions that need to happen next.

Speaker #3: Let me put it into a little bit more detail and show you what I mean by that, right? This slide shows me where we came from and where we're going.

Speaker #3: We started with place. Skyflow understands where and how people work. Workplaces, spaces, resources, presence, and experiences, and maps and locations. Now we are moving into person with beat.

Speaker #3: Employees want fewer applications. Executives want decisions rather than more dashboards. And mid-market businesses want practical AI that produces value today, without having to assemble teams of AI engineers to build it themselves.

Speaker #3: Beat is about personal and team execution. What do I need to accomplish? What has changed? What matters most right now? What should happen next?

Speaker #3: This is the opportunity that we are designing SKY around. So, we're building the agentic AI layer for enterprises to work and grow. And that is our focus.

Speaker #3: How am I going to become more productive? And eventually, what can the platform safely do for me, right, in an enterprise? You want to be in a secure environment.

Speaker #3: Let me put it into a little bit more detail and show you what I mean by that, right? This slide shows me where we came from and where we're going.

Speaker #3: You want to be able to get your stuff done. Now we're adding business through engine room. How does the company find customers? How does it convert demand?

Speaker #3: We started with place. Skyflow understands where and how people work: workplaces, spaces, resources, presence, and experiences—and also maps and locations. Now, we are moving into person with Beat.

Speaker #3: Where is the marketing working? Where is it not working? What is their revenue being lost? All those questions need to get answered. And what action should happen next to grow the business?

Speaker #3: So think about what we are assembling. Place gives us workplace context. Beat gives us personal and team context. Engine room gives us customer and growth context.

Speaker #3: Beat is about personal and team execution. What do I need to accomplish? What has changed? What matters most right now? What should happen next?

Speaker #3: How am I going to become more productive? And eventually, what can the platform safely do for me, right? In an enterprise, you want to be in a secure environment.

Speaker #3: And underneath all these three is one shared sky platform. It senses, it prioritizes, it acts, it verifies, and critically, it learns. And also, it gets it done.

Speaker #3: You want to be able to get your stuff done. Now, we're adding business through Engine Room. How does the company find customers? How does it convert demand?

Speaker #3: We're about the outcome business. We're about context should not just another insight. Context should lead to an outcome. And this is what we're focused on.

Speaker #3: Where is the marketing working? Where is it not working? What revenue is being lost? All those questions need to get answered. And what action should happen next to grow the business?

Speaker #3: It's really creating those amazing outcomes for our clients. So next, I'm going to talk about the market, right? So this is studies taken from one of the vendors, the Grandview Research.

Speaker #3: So think about what we are assembling. Place gives us workplace context. Beat gives us personal and team context. Engine Room gives us customer and growth context.

Speaker #3: And you look at the market surrounding this. Amazing. We're participating in three large categories that are all growing. Digital workplace platforms, enterprise agentic AI, and now marketing automation and growth intelligence.

Speaker #3: And underneath all these three is one shared Sky Platform. It senses, it prioritizes, it acts, it verifies, and—critically—it learns. And also, it gets it done.

Speaker #3: The individual market growth shown here are significant, but the bigger number is the compounding effect is the 75x plus compounding effect of growth over the next couple of years into 2030.

Speaker #3: We're about the outcome business. We're about context—context should not be just another insight. Context should lead to an outcome. And this is what we're focused on: really creating those amazing outcomes for our clients.

Speaker #3: It is not claimed that our addressable market sometimes becomes 75%, but the opportunity for us is 75x. So we're not exposed to only one category now.

Speaker #3: So next, I'm going to talk about the market, right? So these are studies taken from one of the vendors, Grandview Research. And you look at the market surrounding this—amazing.

Speaker #3: We're exposed to three categories. We sit in the intersection of workplace intelligence, agentic AI, and business growth intelligence. And Mike can mention is that the intersection matters.

Speaker #3: We're participating in three large categories that are all growing: digital workplace platforms, enterprise agentic AI, and now marketing automation and growth intelligence. The individual market growth shown here is significant.

Speaker #3: Because enterprises don't ultimately buy AI because AI is interesting. They buy it to make employees more productive, make better decisions, reduce cost, and grow revenue.

Speaker #3: These are precisely the outcomes that these three businesses allow us to attack together. So let me talk about what are we building, right? And we spent a lot of energy and time with our Silicon Valley team, and as we integrate our folks in Australia, they've also been thinking about it.

Speaker #3: But the bigger number is the compounding effect—it is the 75x plus compounding effect of growth over the next couple of years into 2030. It is not claimed that our addressable market sometimes becomes 75%, but the opportunity for us is 75x.

Speaker #3: So we're not exposed to only one category now. We're exposed to three categories. We sit at the intersection of workplace intelligence, agentic AI, and business growth intelligence.

Speaker #3: And the reality is all great minds think together, and we've had a great interaction with our teams. This gets to the heart of what we're building.

Speaker #3: And my convention is that the intersection matters. Because enterprises don't ultimately buy AI because AI is interesting. They buy it to make employees more productive, make better decisions, reduce costs, and grow revenue.

Speaker #3: Across the top, you see the context domains. The work intelligence, the place and person, the growth intelligence, the business. And the future verticals that we can add over time.

Speaker #3: But I wanted to focus I want you to focus on what's underneath. This is the sky agentic platform. The philosophy is simple. Understand the context, recommend the action, get the right approval, complete the outcome.

Speaker #3: These are precisely the outcomes that these three businesses allow us to attack together. So let me talk about what we are building, right? We spent a lot of energy and time with our Silicon Valley team.

Speaker #3: As I mentioned in previous events, Bond is our agentic engine. Bond is a multimodal, multi-agent orchestration system that provides the agentic execution capability. Cortex provides intelligence.

Speaker #3: And as we integrate our folks in Australia, they've also been thinking about it. And the reality is, all great minds think together. And we've had a great interaction with our teams.

Speaker #3: This gets to the heart of what we're building. Across the top, you see the context domains: the work intelligence, the place and person, the growth intelligence, the business.

Speaker #3: Context, knowledge graphs, personalization analytics. And we surround that with the requirements of enterprise actually care about. They care about identity. They care about auditability.

Speaker #3: And the future verticals that we can add over time. But I wanted to focus—I want you to focus—on what's underneath. This is the Sky Agentic Platform.

Speaker #3: They care about human control. They care about connectors. They care about governance. They care about all the things that are important to make an enterprise successful.

Speaker #3: The philosophy is simple: understand the context, recommend the action, get the right approval, and complete the outcome. As I mentioned in previous events, Bond is our agentic engine.

Speaker #3: And that's why we have designed this for the enterprise. We've designed this with all those controls. And we've also integrated with all our partners, all our cloud partners, as you know, we have a strong relationship with Google Cloud, also partner with AWS, and we have also one of our clients using Azure.

Speaker #3: Bond is a multimodal, multi-agent orchestration system that provides the agentic execution capability. Cortex provides intelligence—context, knowledge graphs, personalization, analytics. And we surround that with the requirements that enterprises actually care about.

Speaker #3: So we are multi-cloud, we have access to all their models, all their information, and we're using the best-in-class technology to deliver this agentic operating layer.

Speaker #3: And the most important part of that discussion is we are not betting on sky on one foundational AI model. Models will change. Models will get cheaper.

Speaker #3: They care about identity. They care about auditability. They care about human control. They care about connectors. They care about governance. They care about all the things that are important to make an enterprise successful.

Speaker #3: Models will become more powerful. Our value is the enterprise context orchestration, permissions, actions, and outcomes layer from these models. That's why I call it the operating layer.

Speaker #3: And that's why we have designed this for the enterprise. We've designed this with all those controls, and we've also integrated with all our partners—all our cloud partners.

Speaker #3: The model can provide intelligence. Sky makes that intelligence useful inside the enterprise. We are the outcomes. We are the actions. And that's what we're focused on.

Speaker #3: As you know, we have a strong relationship with Google Cloud, and we are also partnered with AWS. Additionally, one of our clients is using Azure.

Speaker #3: So we are multi-cloud. We have access to all their models, all their information. And we're using the best-in-class technology to deliver this agentic operating layer.

Speaker #3: Another key part of this as we looked at engine room and other opportunities to partner with folks is that this architecture that we built gives us tremendous leverage.

Speaker #3: And the most important part of that discussion is we're not betting on just one foundational AI model. Models will change. Models will get cheaper.

Speaker #3: We don't have to build a completely different technology stack every time we enter a new use case. The same orchestration layer can support workplace agents, can support growth agents, analytics agents, automation agents.

Speaker #3: Models will become more powerful. Our value is the enterprise context, orchestration, permissions, actions, and outcomes layer for these models. That's why I call it the operating layer.

Speaker #3: And eventually, industry-specific agents. A meeting agent and an attribution agent may solve way different customer problems, but underneath, they need many of the same capabilities.

Speaker #3: The model can provide intelligence. Sky makes that intelligence useful inside the enterprise. We are the outcomes. We are the actions. And that's what we're focused on.

Speaker #3: They need the data. They need the context. They need the permissions. They need the workflow orchestration. They need auditability. And the ability to complete work in the system where that work belongs.

Speaker #3: Another key part of this, as we looked at Engine Room and other opportunities to partner with folks, is that this architecture we built gives us tremendous leverage.

Speaker #3: That is where I believe the leverage comes from. One platform, many specialized agents, real business outcomes. And the more repeatable those agents become, the more efficiently we can take them to the mid-market.

Speaker #3: We don't have to build a completely different technology stack every time we enter a new use case. The same orchestration layer can support workplace agents, growth agents, analytics agents, and automation agents.

Speaker #3: So that's where we're really focused on is we've built a really strong technology architecture, and now we're looking for with that amazing product we're looking for the distribution model.

Speaker #3: And eventually, industry-specific agents. A meeting agent and an attribution agent may solve very different customer problems, but underneath, they need many of the same capabilities.

Speaker #3: And this is where our new friends at engine room come in. So as I think about engine room, I think I mentioned in the earnings call, but I want to reiterate.

Speaker #3: They need the data. They need the context. They need the permissions. They need the workflow orchestration. They need auditability, and the ability to complete work in the system where that work belongs.

Speaker #3: It is strategically super important for us. It is simply not an acquisition that added revenue. Engine room changes how we can take sky to market.

Speaker #3: That is where I believe the leverage comes from: one platform, many specialized agents, real business outcomes. And the more repeatable those agents become, the more efficiently we can take them to the mid-market.

Speaker #3: Sky gives us the enterprise anchor. Technology-proven in complex environments. Engine room gives us a mid-market customer base recurring revenue commercial data and people who understand how to drive measurable business outcomes.

Speaker #3: So that's where we're really focused. We've built a really strong technology architecture, and now we're looking— with that amazing product— we're looking for the distribution model.

Speaker #3: And Australia gives us an excellent launch pad. We can launch, learn, and scale. We can work directly with businesses in trades and field services, construction, automotive, healthcare, professional services and manufacturing.

Speaker #3: And this is where our new friends at Engine Room come in. As I think about Engine Room—I think I mentioned this in the earnings call, but I want to reiterate.

Speaker #3: These are incredibly important parts of the real economy. A plumber doesn't need another chatbot. A construction company doesn't need another AI demonstration. A healthcare operator doesn't need another dashboard.

Speaker #3: It is strategically super important for us. It is simply not an acquisition that added revenue. Engine Room changes how we can take Sky to market.

Speaker #3: Sky gives us the enterprise anchor—technology proven in complex environments. Engine Room gives us a mid-market customer base with current revenue, commercial data, and people who understand how to drive measurable business outcomes.

Speaker #3: They're very practical folks. They need more customers. They need faster response. They need higher employee productivity. They need better visibility in what is driving All right.

Speaker #3: They're very practical folks. They need more customers. They need faster response. They need better scheduling. They need lower acquisition costs. They need higher employee productivity.

Speaker #3: They need better visibility into what is driving revenue. This is where practical vertical AI becomes incredibly powerful. Engine Room gives us more than 50 customer relationships and a recurring revenue foundation.

Speaker #3: Our objective is to identify the workflows that repeatedly create value, prioritize them on the Sky platform, and distribute them more broadly. Services help us discover the problem.

Speaker #3: So next, let me talk about a little bit more detail about the combined platform, right? All of these strategies and these product visions ultimately have to translate into economics.

Speaker #3: Software gives us the skill, so this is why I'm super excited about Engine Room. It's giving us a head start into the mid-market strategy that we've had.

Speaker #3: And I'm going to go a little bit more deeper. I know I went a little bit on the earnings call, but the acquisition gave us the scale.

Speaker #3: It gave us that thumb in revenue. Now, sky 2.0 has to give us operating leverage. Today, we have that combined revenue north of 12 million.

Speaker #3: We're working closely with them this quarter to start identifying customers that have already shown a lot of great interest. And as we get Flow, Beat, Events, and other products that Chris is going to go through, there's a huge opportunity to leverage that channel.

Speaker #3: We have enterprise customers on the sky side. We're growing those customers. We have those 50 mid-market relationships to engine room. We have recurring revenue.

Speaker #3: We have data. We have distribution. The next phase is about pulling four levers. Number one lever is grow and expand the existing businesses. And both businesses are really working really well.

Speaker #3: All right. So next, let me talk in a little bit more detail about the combined platform, right? All of these strategies and these product visions ultimately have to translate into economics.

Speaker #3: The enterprise business is expanding and engine room customer growth is happening. Secondly, cross-sell and distribute across the combined customer base. That's job one, and we're doing that right now as we speak.

Speaker #3: And I'm going to go a little bit deeper. I know I touched on this a bit during the earnings call. But the acquisition gave us the scale.

Speaker #3: It gave us that jump in revenue. Now, Sky 2.0 has to give us operating leverage. Today, we have that combined revenue north of $12 million.

Speaker #3: Third is the exciting part of prioritizing the AI and new modules increasing the software component of our revenue, which is already 95%, but now growing it in the new AI economy.

Speaker #3: We have enterprise customers on the Sky side. We're growing those customers. We have those 50 mid-market relationships in Engine Room. We have recurring revenue.

Speaker #3: And fourth, creating that operating leverage as the company scales. And we talked about it's already starting to show the signs in Q2 here. This means that ultimately means that revenue should grow faster than the infrastructure required to support it.

Speaker #3: We have data. We have distribution. The next phase is about pulling four levers. The number one lever is to grow and expand the existing businesses. And both businesses are really working really well.

Speaker #3: Our ambition is very clear. Higher recurring revenue, higher software mix, higher gross margins. More revenue per customer, and a path towards breakeven and then profitable growth.

Speaker #3: The enterprise business is expanding, and engine room customer growth is happening. Secondly, cross-sell and distribute across the combined customer base—that's job one. And we're doing that right now as we speak.

Speaker #3: So the acquisition created the scale. The platform has to create the leverage. And that's what we're focused on executing. And I'm pretty excited that this is a path that we're on.

Speaker #3: Third is the exciting part of prioritizing the AI and new modules—continuing to increase the software component of our revenue, which is already at 95%, but now growing it in the new AI economy.

Speaker #3: As I said on the earnings call, we have all those metrics. We're diligently working on them as part of the integration. I'm showing some directional synergy targets that the team has.

Speaker #3: And fourth, creating that operating leverage as the company scales. And we talked about it’s already starting to show signs in Q2 here. This means that, ultimately, revenue should grow faster than the infrastructure required to support it.

Speaker #3: We're already realizing some of those synergy targets in the second half of this year. Next year, we believe they're going to be more, not only on cost synergy, but also revenue synergy.

Speaker #3: Our ambition is very clear: higher recurring revenue, higher software mix, higher gross margins, more revenue per customer, and a path towards breakeven and then profitable growth.

Speaker #3: And then finally, the flywheel effect with the sky 2.0 product will really implement much higher growth factors here. So all of this is great plans, but none of it really happens unless I have a great team to execute.

Speaker #3: So the acquisition created the scale. The platform has to create the leverage. And that's what we're focused on executing. I'm pretty excited that this is the path we're on.

Speaker #3: I'm super excited to introduce some of the team members here. We're working on a very lean operating model. Chris is running enterprise business in North America for us.

Speaker #3: As I said on the earnings call, we have all those metrics. We're diligently working on them as part of the integration. I'm showing some directional synergy targets that the team has.

Speaker #3: Adam is taking on Australasia as well as the engine room business. And then Melissa has stepped up as being our interim CFO. We're also have proud to have a global CTO team.

Speaker #3: We're already realizing some of those synergy targets in the second half of this year. Next year, we believe there are going to be more, not only on cost synergy, but also revenue synergy.

Speaker #3: And then, finally, the flywheel effect with the Sky 2.0 product will really implement much higher growth factors here. So, all of this is great plans, but none of it really happens unless I have a great team to execute.

Speaker #3: That brings together technical leadership across Silicon Valley, Canada, Australia, and Southeast Asia. And that is important. AI innovation is global. Our customers are global.

Speaker #3: Our engineering capabilities should be global as well. This structure is designed around speed, accountability, and execution. We don't want any unnecessary organizational layers. We want talented people close to the customers globally, close to technology, and close to the results.

Speaker #3: I'm super excited to introduce some of the team members here. We're working on a very lean operating model. Chris is running enterprise business in North America for us.

Speaker #3: Adam is taking on Australasia as well as the engine room business. And then Melissa has stepped up as our interim CFO. We are also proud to have a global CTO team.

Speaker #3: So that's where we believe we have a huge opportunity and so anyway, I'm super excited to introduce the team. So I'm going to transition now to Chris, who's going to talk about the North America and enterprise business.

Speaker #3: That brings together technical leadership across Silicon Valley, Canada, Australia, and Southeast Asia. And that is important: AI innovation is global. Our customers are global.

Speaker #3: Chris, go ahead.

Speaker #2: Well, thank you, Kerem. And welcome all. Chris Wiegand, and I'm general manager of North America. I'll let you know, I am an entrepreneur at heart, and I couldn't tell you how excited I am about this whole AI transformation.

Speaker #2: It's truly changing things. I'm sure you have in your personal life, but especially in the workplaces. And what's also exciting, just on the tail of that, we've had the best year we've ever had.

Speaker #3: So that's where we believe we have a huge opportunity. Anyway, I'm super excited to introduce the team, so I'm going to transition now to Chris, who's going to talk about the North America and Enterprise business.

Speaker #2: We've signed the largest deals I'm going to take you through. We've got our 2.0 product deployed and working. We've got a new module I want to tell you about in our events.

Speaker #2: And then Kerem also told you a little bit about the new product feat. So Kerem's been telling you all about strategy, and where we what our vision is.

Speaker #3: Chris, go ahead.

Speaker #1: Well, thank you, Khurram. And welcome, all. Chris Wiegand, and I'm General Manager of North America. I'll let you know, I am an entrepreneur at heart.

Speaker #2: What I want to do for the next 20 minutes, I'm going to tell you through what's happening on the ground. How are we doing our business?

Speaker #1: And I couldn't tell you how excited I am about this whole AI transformation. It's truly changing things. I'm sure you have in your personal life as well.

Speaker #2: What are the customers all about? And most importantly, we've got some live videos that we've recorded to show you the product itself, and then we're going to go through and talk about what's the rest of the year look and how are we going to do it.

Speaker #1: But especially in the workplaces. And what's also exciting, just on the tail of that, we've had the best year we've ever had. We've signed the largest deals—I'm going to take you through them.

Speaker #2: OK, so what I really want to emphasize here is there's not names on the page, but these are the largest and biggest companies in the world, some of them.

Speaker #1: We've got our 2.0 product deployed and working. We've got a new module I want to tell you about in our events. And then Khurram also told you a little bit about the new product beat.

Speaker #2: They're leaders in their space. And I'll tell you this. They have gone through super these are some of the toughest RFPs and diligence processes you can go through.

Speaker #1: So Khurram's been telling you all about strategy and what our vision is. What I want to do for the next 20 minutes is take you through what's happening on the ground.

Speaker #1: How are we doing our business? What are the customers all about? And most importantly, we've got some live videos that we've recorded to show you the product itself.

Speaker #1: And then we're going to go through and talk about what the rest of the year looks like and how we're going to do it.

Speaker #2: And so we're closing this right now. They're starting at the end of this year, so there's going to be a quick turn on our implementation.

Speaker #1: OK. So what I really want to emphasize here is there aren't names on the page, but these are the largest and biggest companies in the world—some of them.

Speaker #1: They're leaders in their space. And I'll tell you this: they have gone through super diligent, "super diligence" we'll call it. These are some of the toughest RFPs and diligence processes you can go through.

Speaker #1: And that's how it should be, right? We're working with very secure, complex environments. And so, by these customers doing this, they've really gone out to market.

Speaker #1: They have the resources. They can choose whoever they want to. And by sandbox trials, by many, many questions and answers, and meetings, we've come out on top.

Speaker #1: So that's the pattern I really want you to know — we keep winning in the regulated environments, the enterprise environments. These are, again, some of the toughest places to get your products deployed.

Speaker #2: Again, five-figure number of users. Very similar use cases in terms of what they're doing. And again, they're starting with an entire population that we're going to go live with.

Speaker #1: So I'll take you through, sort of from left to right here. One of our biggest wins this year is a top financial institution—Eric, actually global.

Speaker #2: Next is a leading US insurer. I'm going to spend a little bit more time on this because this is going to tell you about how we deploy.

Speaker #2: This is an interesting customer for many reasons. One, it's really our bridge to the mid-market. So it's a few thousand users. We're still in an enterprise environment, but this is how we really took our product and learned how are we going to productize this so we're configuring not making custom code.

Speaker #1: They've got dozens of sites around the world, and thousands of users that are going to be coming online. This is actually more than a 12-month pursuit.

Speaker #1: And again, they went out to market, and Sky came out on top. Next, we have a global asset manager, so we're closing this right now.

Speaker #2: And I'm going to talk more about that. And they're going to go live in September. They've got a brand new headquarters, and we're in deployment testing for that right now.

Speaker #1: They're starting at the end of this year, so there's going to be a quick turn on their implementation. Again, five-figure number of users—very similar use cases in terms of what they're doing.

Speaker #2: And then let's not forget our amazing install base. We've got enterprise customers today that are choosing to stay with us. Same rigorous environment. We had one of our largest financial services customers renew.

Speaker #1: And again, they're starting with an entire population that we're going to go live with. Next is a leading US insurer, and I'm going to spend a little bit more time on this because this is going to tell you about how we deploy.

Speaker #2: We had our largest media and entertainment company. They renewed and expanded. And so where is this all going? This is all leading to more revenue.

Speaker #1: This is an interesting customer for many reasons. One, it's really our bridge to the mid-market, so it's a few thousand users. We're still in an enterprise environment.

Speaker #2: That's the goal. And so not giving you guidance, but directionally, the new customers are coming online. The things that we're not even seeing yet in terms of revenue, it's about a third uplift.

Speaker #1: But this is how we really took our product and decided and learned how we were going to productize this, so we're configuring, not making custom code.

Speaker #2: So that's pretty significant when you think about it. And in addition to the other things I'm going to talk you through here. All right, so validation is really the key here.

Speaker #1: And I'm going to talk more about that. And they're going to go live in September. They've got a brand new headquarters, and we're in deployment testing for that right now.

Speaker #1: And then let's not forget our amazing install base. We've got enterprise customers today that are choosing to stay with us—same rigorous environments. We had one of our largest financial services customers renew.

Speaker #2: You can go win these deals, but you have to deliver them. And that's really what our customers are expecting is exactly what we're doing.

Speaker #2: So this is the company I'm going to take you through sort of a quick timeline of how we're delivering for this leading US insurer.

Speaker #1: We had our largest media and entertainment company. They renewed and expanded. So where is this all going? This is all leading to more revenue.

Speaker #2: And again, it's a brand new headquarters for them. So it starts out, we have an enterprise agreement. And this is very detailed scope of work.

Speaker #1: That's the goal. And so, directionally, the new customers that are coming online—the things that we're not even seeing yet in terms of revenue—it's about a one-third uplift.

Speaker #2: We understand exactly what we're delivering, how we're going to do it. And then we go and build it. So with that, we have integrations into their core systems.

Speaker #1: So that's pretty significant when you think about it, in addition to the other things I'm going to talk you through here. All right.

Speaker #2: Remember, the pull value of what we do here and flow, Sky, is we're taking disparate systems, and we're putting it all into one cohesive system that an employee can just get what they need quickly and easily.

Speaker #1: So validation is really the key here. You can go win these deals, but you have to deliver them. And that's really what our customers are expecting—exactly what we're doing.

Speaker #2: And you're going to see that in the demo. Now we're in testing. So we deployed 2.0 to them. We've got most of the integrations done with a brand new headquarters, as you can imagine.

Speaker #1: So this is the company. I'm going to take you through a quick timeline of how we're delivering for this leading U.S. insurer.

Speaker #2: There's things that are staged. So right in the next 30 days, we've got really important next steps in terms of finalizing testing, but I can tell you the client is extremely happy.

Speaker #1: And again, it's a brand new headquarters for them. So, it starts out, we have an enterprise agreement, and this is a very detailed scope of work.

Speaker #1: We understand exactly what we're delivering, how we're going to do it, and then we go and build it. So, with that, we have integrations into their core systems.

Speaker #2: We're right on schedule. And then we're going to scale. And so that goes live to the population. And there's a few really important points I want you to remember here.

Speaker #1: Remember, the pull value of what we do here at Flow, Sky, is we're taking disparate systems and we're putting it all into one cohesive system so that an employee can just get what they need quickly and easily.

Speaker #2: This is our point that we've really transitioned from custom code. This is not custom development for a customer. This is configuration, which means it goes faster.

Speaker #1: And you're going to see that in the demo. Now we're in testing, so we deployed 2.0 to them. We've got most of the integrations done with a brand new headquarters, as you can imagine.

Speaker #2: OK, so this is how we're going to deploy to the mid-market as well. We've also, if you've been on our earnings calls before, we've talked about how we're moving away from the big one-time upfront fees to and campus fees to per-user software.

Speaker #1: There are things that are staged. So, right in the next 30 days, we've got really important next steps in terms of finalizing testing, but I can tell you the client is extremely happy.

Speaker #2: The market is demanding value-based pricing. And value comes from people using the product. So when we deploy it, we expand it through utilization and through people actually adopting the product.

Speaker #1: We're right on schedule, and then we're going to scale, and so that goes live to the population. There are a few really important points I want you to remember here.

Speaker #2: So we've got a common goal with our customers to get everybody using it so they realize value, we realize revenue. And so again, a key message here is that we've taken what we've learned in the enterprise, the really complicated environments, and we're taking that into more deployment and into a repeatable, scalable model that I'll talk you through a little bit further here.

Speaker #1: This is our point: that we've really transitioned from custom code. This is not custom development for a customer; this is configuration, which means it goes faster.

Speaker #1: So this is how we're going to deploy to the mid-market as well. We've also—if you've been on our earnings calls before—we've talked about how we're moving away from the big, one-time upfront fees and campus fees to per-user software.

Speaker #2: OK, so what I want to also as I'm going to introduce you to the products and Kerem has already, I want to highlight a point that we've proven ourselves in the enterprise.

Speaker #1: The market is demanding value-based pricing. And value comes from people using the product. So, when we deploy it, we expand it through utilization and through people actually adopting the product.

Speaker #2: And that's revenue. That's great. But what it's also doing is it's giving us the ability to productize what we've done and go down market.

Speaker #1: So we've got a common goal with our customers to get everybody using it so they realize value and we realize revenue. And so again, a key message here is that we've taken what we've learned in the enterprise, the really complicated environments.

Speaker #2: So I'm going to work through the product that is out there today flow. The ones that our customers are using. The book spaces to wayfind, to interact, to get news.

Speaker #1: And we're taking that into more deployment and into a repeatable, scalable model that I'll talk you through a little bit further here. Okay, so what I want to do, also, as I'm going to introduce you to the products—and Khurram has already—I want to highlight a point: that we've proven ourselves in the enterprise.

Speaker #2: This is what's out there. That's what's flow. And we've got this transition. Now that we've built 2.0 to transition those customers and new customers onto that.

Speaker #2: All the data that they're creating goes into Sky View. View is our analytics platform. So this is what's not just dashboards, and this is going to be one of the demos as well.

Speaker #2: You're going to see it's taking that operational data and turning it into insights. That's really exciting. Next, events module. This is a brand new product.

Speaker #1: And that's revenue. That's great. But what it's also doing is giving us the ability to productize what we've done and go down market.

Speaker #2: It's coming out in just a few weeks. We'll be GA in September. And we've solved a major industry problem and I bet you everybody who works in enterprise is going to recognize this right away.

Speaker #1: So I'm going to work through the product that is out there today— the ones that our customers are using. They book spaces to wayfind, to interact, to get news.

Speaker #2: I'm not going to talk about it now because I've got a couple of minutes. I'm going to just go into more detail on that.

Speaker #1: This is what's out there. That's what's flowing. And we've got this transition. Now that we've built 2.0, it's to transition those customers and new customers onto that.

Speaker #2: And then Kerem had also told you about new product Beat coming. So Beat is really this tool that keeps everything on track, starting with the personal level.

Speaker #1: All the data that they're creating goes into Sky View. View is our analytics platform, so this is not just dashboards. This is going to be one of the demos as well.

Speaker #2: This is a productivity tool. And I'll tell you that people working in companies today are overwhelmed with the number of messages they're getting. They've got systems for Jira, Slack, Teams.

Speaker #1: You're going to see it's taking that operational data and turning it into insights, so that's really exciting. Next, events module. This is a brand new product.

Speaker #2: They've got things coming at them. There's duplication all over the place. And it becomes anxiety. They don't know what to do next. So we've created a system that keeps everything moving, keeps you prioritized, on what's most important next, and also prepares or does the work for you to keep the team moving.

Speaker #1: It's coming out in just a few weeks. We'll be GA in September. And we've solved a major industry problem. I bet everybody who works in enterprise is going to recognize this right away.

Speaker #1: I'm not going to talk about it now, because I've only got a couple of minutes. I'll go into more detail on that later.

Speaker #2: So stand by for that one. That's coming in Q4, and we'll certainly tell you all about that as soon as it's live. What I also want to make sure that we recognize is that we've got the same agentic platform driving all of this.

Speaker #1: And then Khurram had also told you about the new product, Beat, coming. So, Beat is really this tool that keeps everything on track, starting at the personal level.

Speaker #1: This is a productivity tool. And I'll tell you that people working in companies today are overwhelmed with the number of messages they're getting. They've got systems for Jira, Slack, Teams.

Speaker #2: So underneath all of this is a Sky agentic platform. So this is the thing that's going to really as you can see here, sense what's the proximity, what's happening, what's the priority.

Speaker #1: They've got things coming at them. There's duplication all over the place, and it becomes anxiety. They don't know what to do next. So we've created a system that keeps everything moving, keeps you prioritized on what's most important next.

Speaker #2: Act, meaning do something for you. That's what agentic means. It's not just giving you a message and reminding you. It's actually in a lot of cases executing on something.

Speaker #2: And then verifying. So it may give you a plan, and you can approve that plan. So what we're going to do now, we're going to go into two videos.

Speaker #1: And also prepares or does the work for you to keep the team moving. So stand by for that one. That's coming in Q4, and we'll certainly tell you all about that as soon as it's live.

Speaker #2: They are live demos of both flow, the we'll call it the Nomi scenario. This is an employee's view of how they're going to go with their day.

Speaker #1: What I also want to make sure that we recognize is that we've got the same agentic platform driving all of this. So, underneath all of this is a Sky agentic platform.

Speaker #2: You're going to hear me talking conversationally with the platform to do several use cases. That's about two or three minutes. And then we're going to transition to the next video which is View, our Sky View analytics.

Speaker #1: So, this is the thing that's going to really, as you can see here, sense what's the proximity, what's happening, what's the priority. 'Act' meaning do something for you.

Speaker #1: That's what agentic means. It's not just giving you a message and reminding you; it's actually, in a lot of cases, executing on something and then verifying.

Speaker #2: And this is from the manager's perspective. So they're going to be there asking the strategic and insights that they want to get out of the data that they have.

Speaker #2: So with that, David, if you wouldn't mind, let's go to the videos, and I'll see you all back in about five minutes.

Speaker #1: So, it may give you a plan, and you can approve that plan. So, what we're going to do now is go into two videos.

Speaker #1: There are live demos of both flows, and we'll call it the Nomi scenario. This is an employee's view of how they're going to go about their day.

Speaker #1: This is our Sky Enterprise platform, Flow. And it's what's live in production as some of the largest enterprises in America and around the globe.

Speaker #1: So one thing to note before we start, the solution is powered by actually years of workplace data. Getting analyzed, continuously by the platform to drive my employee experience, where I like to sit, who I like to work with, how I use the building.

Speaker #1: You're going to hear me talking conversationally with the platform to do several use cases. That's about two or three minutes, and then we're going to transition to the next video, which is View or Sky View analytics.

Speaker #1: And so all of this intelligence you're about to see isn't actually just configured. It's learned. And this is a key differentiator for Sky. Now, before I jump into the agentic part of this, what we're looking at here is the web desktop version.

Speaker #1: And this is from the manager's perspective. So they're going to be there asking about the strategy and insights that they want to get out of the data that they have.

Speaker #1: So, with that, David, if you wouldn't mind, let's go to the videos. And I'll see you all back in about five.

Speaker #1: We'd see the exact same thing on mobile, the way a feature parity between all of them. So no matter where somebody is or what device they're using, they're going to get the same information.

Speaker #2: This is our Sky Enterprise platform flow, and it's what's live in production at some of the largest enterprises in America and around the globe.

Speaker #1: And I've configured this to be personalized to me, the things that I want to know about, the things that I want to get to quickly.

Speaker #2: So one thing to note before we start: the solution is powered by, actually, years of workplace data—getting analyzed continuously by the platform to drive my employee experience: where I like to sit, who I like to work with, how I use the building.

Speaker #1: And all of this is on my dashboard, which each person can configure themselves. So let's jump into the agentic use cases. And what I love about this is it's totally conversational, just how I like to ask questions and get answers right away.

Speaker #2: And so, all of this intelligence you're about to see isn't actually just configured—it's learned. And this is a key differentiator for Sky. Now, before I jump into the agentic part of this, what we're looking at here is the web desktop version.

Speaker #1: It's doing all the heavy lifting in the back end. So I'll go through a few use cases that are pretty typical in a workplace.

Speaker #2: We'd see the exact same thing on mobile, with feature parity between all of them. So, no matter where somebody is or what device they're using, they're going to get the same information.

Speaker #1: I'm coming into the office tomorrow to meet with Tyler to work on a charging port near him.

Speaker #2: And I've configured this to be personalized to me—the things that I want to know about, the things that I want to get to quickly.

Speaker #3: Done. I booked desk SRW03 for tomorrow, August 13th. Would you like me to schedule your meeting with Tyler as well?

Speaker #2: And all of this is on my dashboard, which each person can configure themselves. So let's jump into the agentic use cases. What I love about this is it's totally conversational, just how I like to ask questions and get answers right away.

Speaker #1: So notice a couple of things here that I did in the demo. I didn't tell it who Tyler was. I'm meeting with Tyler Robbins, but it knew that because I always work with Tyler or I'll work with him pretty often.

Speaker #2: It's doing all the heavy lifting in the back end, so I'll go through a few use cases that are pretty typical in a workplace.

Speaker #1: It was able to search for where is he, proximity matters. So find a spot that's near him. But it also had another variable. It needed to have a charging port.

Speaker #2: I'm coming into the office tomorrow to meet with Tyler to work on a project. Book me a desk with a charging port near him.

Speaker #1: So all of this stuff is going on in the background. Let's just see how the system handles it when I want to make a change.

Speaker #3: Done. I booked desk SRW03 for tomorrow, August 13th. Would you like me to schedule your meeting with Tyler as well?

Speaker #1: I now need to sit with Dana tomorrow. We're working on an urgent project. Can you change my desk?

Speaker #3: Done. I've moved you from SRW03 to CXE01 for tomorrow.

Speaker #2: So notice a couple of things here that I did in the demo. I didn't tell it who Tyler was. I'm meeting with Tyler Robbins.

Speaker #1: OK, once again, I didn't say who Dana was. It knows who Dana is because I usually work with her. It went in in the background.

Speaker #2: But it knew that, because I always work with Tyler, or I work with him pretty often. It was able to search for where he is. Proximity matters.

Speaker #1: It went to the calendar system. It canceled the meeting that I or the desk that I had already reserved. And it booked me a new one and kept the attribute of having a charging port.

Speaker #2: So, find a spot that's near him. But it also had another variable—it needed to have a charging port. So, all of this stuff is going on in the background.

Speaker #1: So this, again, really demonstrates contextual and spatial awareness. Here's another important question it might ask. How do I get to the men's bathroom from my desk?

Speaker #2: Let's just see how the system handles it when I want to make a change. I now need to sit with Dana tomorrow. We're working on an urgent project.

Speaker #2: Can you change my desk?

Speaker #3: It's on the map. From CXE01, go straight ahead and the men's bathroom is just down the hall on level three.

Speaker #3: Done. I've moved you from SRW03 to CXE01 for tomorrow.

Speaker #1: So what we have that's really special and different I would call this a key differentiator is the mapping platform fully embedded into the system.

Speaker #2: OK, once again, I didn't say who Dana was. It knows who Dana is because I usually work with her. It went in in the background.

Speaker #2: It went to the calendar system. It canceled the meeting that I, or the desk that I, had already reserved. And it booked me a new one and kept the attribute of having a charging port.

Speaker #1: So when we need real spatial context, or even wayfinding directions, we can do it like this, just as a thumbnail and show you contextually.

Speaker #1: Or you could start a full wayfinding experience and yet turn by turn, like you driving your car, it tells you when to turn left, when to turn right.

Speaker #2: So this again really demonstrates contextual and spatial awareness. Here's another important question it might ask: How do I get to the men's bathroom from my desk?

Speaker #1: So it really understands the building and it definitely understands where you are. And that's the power of Sky Flow. It's constantly learning your behaviors.

Speaker #3: It's on the map. From CXE01, go straight ahead, and the men's bathroom is just down the hall on level three.

Speaker #1: It's constantly getting smarter. And it just becomes more and more personalized. This is why people love to use Sky Flow every day. So this is our analytics workspace, Sky View.

Speaker #2: So, what we have that's really special and different—I would call it a key differentiator—is the mapping platform fully embedded into the system.

Speaker #2: So when we need real spatial context, or even wayfinding directions, we can do it like this—just as a thumbnail—and show you contextually.

Speaker #2: Or you could start a full wayfinding experience and get turn-by-turn, like when you're driving your car—it tells you when to turn left, when to turn right.

Speaker #1: And it's a real workplace. What we're looking at here, what we're going to go through, is four campuses of both 27,000 employees and every desk, room, and booking is feeding it live.

Speaker #2: So, it really understands the building, and it definitely understands where you are. And that's the power of Sky Flow—it's constantly learning your behaviors.

Speaker #1: And you can see this from the numbers. There's about 10,000 active users. 38% desk utilization. It's a nice dashboard, but dashboards don't make decisions.

Speaker #2: It's constantly getting smarter, and it just becomes more and more personalized. This is why people love to use Sky Flow every day. This is our analytics workspace, Sky View.

Speaker #1: So instead of clicking through reports, I'm just going to go and ask it questions, out loud, the way a manager actually would. Show me the weekly active users over the last six months.

Speaker #3: Adoption is strong and steady, around 17,000 employees use the workplace app every week. And it has held there for six straight months. Peaking at 18,918.

Speaker #2: And it's a real workplace. What we're looking at here, what we're going to go through, is four campuses—about 27,000 employees. And every desk, room, and booking is feeding in live.

Speaker #3: Week of April 13th, chart. The weekly active users line shows a consistent pattern around 17K users, with a notable peak in mid-April and a slight dip toward the end of the observed period.

Speaker #2: And you can see this from the numbers: there are about 10,000 active users, 38% desk utilization. It’s a nice dashboard, but dashboards don’t make decisions.

Speaker #1: OK, so I got there's 17,000 people a week, and it's held for six months. That's real adoption. That's great. But a chart doesn't tell me what to do about anything.

Speaker #2: So instead of clicking through reports, I'm just going to go and ask it questions out loud the way a manager actually would. Show me the weekly active users over the last six months.

Speaker #1: So let's push on it a little bit. Which floors were consistently underused the last quarter?

Speaker #3: Adoption is strong and steady—around 17,000 employees use the workplace app every week, and it has held there for six straight months, peaking at 18,918.

Speaker #3: Seven floors at CXA HQ sat almost empty last quarter, even at their busiest moment of the day. R&D 2T peaked at just 2% full, and HQ 1B at 5%.

Speaker #3: The rest ran between 10% and 19%. Anything under the 40% line is space that isn't earning its keep. Chart. Want me to dig into why those floors are so quiet?

Speaker #2: OK, so I got that there's 17,000 people a week, and it's held for six months. That's real adoption. That's great. But a chart doesn't tell me what to do about anything.

Speaker #1: All right, before we do that, so seven floors, just like that. Notice I didn't tell it where to look. It went into our own operating data and found the problem floors on its own.

Speaker #2: So let's push on it a little bit. Which floors were consistently underused the last quarter?

Speaker #1: So obviously, the next question is, why? What's driving the low utilization on those floors?

Speaker #3: It's the day-of-week pattern. Fridays sit nearly empty at 9% occupancy, and Mondays are light at 17%. While Tuesday through Thursday carry the campus at 23.

Speaker #3: Seven floors at CXA HQ sat almost empty last quarter. Even at their R&D, 2T peaked at just 2% full and HQ1B at 5%. The rest ran between 10% and 19%.

Speaker #3: To 26%. The underuse is concentrated at the start and end of the week. Exactly the days a consolidation would reclaim.

Speaker #3: Anything under the 40% line is space that isn't earning its keep—chart. Want me to dig into why those floors are so quiet?

Speaker #1: OK, so now we know that Mondays and Fridays are the culprit. That's not a reporting error. Now we know it's a real diagnosis. We've got the data.

Speaker #2: All right. Before we do that—so, seven floors, just like that. Notice I didn't tell it where to look. It went into our own operating data and found the problem floors on its own.

Speaker #1: All right, now the question a CFO would ask. If we consolidated those floors, could rest be absorbed for the demand we have?

Speaker #2: So obviously the next question is, why? What's driving the low utilization on those floors?

Speaker #3: Yes, comfortably. The seven near-empty floors carry only about 161 desks of real peak demand. At a healthier floors have roughly 1,180 desks. Of headroom to take them.

Speaker #3: It's the day-of-week pattern. Fridays sit nearly empty at 9% occupancy, and Mondays are light at 17%, while Tuesday through Thursday carry the campus at 23% to 26%.

Speaker #3: You could hand back all seven floors and still leave about 1,000 desks of slack. So nearly half the floors examined read as surplus, with no hit to employee experience.

Speaker #3: The underuse is concentrated at the start and end of the week—exactly the days a consolidation would reclaim.

Speaker #2: OK, so now we know that Mondays and Fridays are the culprit. That's not a reporting error. Now we know it's a real diagnosis. We've got the data.

Speaker #1: All right, that's the part that I love. I didn't just say yes. It checked real peak demand, checked the headroom on the other floors, and made sure employees wouldn't feel it.

Speaker #2: All right. Now the question a CFO would ask: If we consolidated those floors, could the rest be absorbed for the demand we have?

Speaker #1: All in one answers. OK, you went from is anyone even using this to here's what to do about it in just a couple of minutes.

Speaker #3: Yes, comfortably. The seven near-empty floors carry only about 161 desks of real peak demand, and the healthier floors have roughly 1,180 desks of headroom to take them.

Speaker #1: Just by asking. Just in this conversation. That's what we mean by agentic analytics. The company owns data, and turns it into decisions. OK, I'm so glad everybody got to see that.

Speaker #3: You could hand back all seven floors and still leave about 1,000 desks of slack. So nearly half the floors examined read as surplus, with no hit to employee experience.

Speaker #2: All right. That's the part that I love. I didn't just say yes. It checked real peak demand, checked the headroom on the other floors, and made sure employees wouldn't feel it.

Speaker #1: And I get excited every time I get to demo that. Certainly feels like we've got the hotcakes. I say that because this is how people want to work.

Speaker #2: All-in-one answers. OK, you went from 'Is anyone even using this?' to 'Here's what to do about it' in just a couple of minutes.

Speaker #1: They don't want the friction of having to dive into stuff. And even if you make something super easy, and user-friendly, you just you'd rather ask it through a conversation.

Speaker #2: Just by asking—just in this conversation. That’s what we mean by agentic analytics. The company-owned data, and turns it into decisions. OK, I’m so glad everybody got to see that.

Speaker #1: So the parking lot that and I'm going to move on to events. And so this is our newest module. And what we see on the screen here looks like chaos because it is.

Speaker #1: This is what people are living in the enterprise environments when they're talking about managing events. And I'm not really referring to thousands of people at a large public event.

Speaker #2: And I get excited every time I get to demo that. It certainly feels like we've got the hotcakes. I say that because this is how people want to work.

Speaker #1: Yeah, those are confusing too, but that's not what we're doing here. What we're doing is we're helping people manage events that are happening at the workplace.

Speaker #1: They happen every single day in all of our customers both mid-level and in the enterprise. They're going to be all hands calls. They're going to be sales kickoffs.

Speaker #2: They don't want the friction of having to dive into stuff. And even if you make something super easy and user-friendly, you'd still rather ask it through a conversation.

Speaker #1: They're going to be training events. And this is really managing the part that you need a room that you can't request yourself. It's not a reservable space.

Speaker #2: So, let's parking lot that, and I'm going to move on to events. This is our newest module, and what we see on the screen here looks like chaos—because it is.

Speaker #1: And so for the people that manage this on the other side, the admins, they're dealing with everything you see on the screen. They're going to get a calendar invite or a request.

Speaker #2: This is what people are experiencing in enterprise environments when they're talking about managing events. And I'm not really referring to thousands of people at a large public event.

Speaker #1: They're going to get an email. They're going to have to open up a ticket in the catering system, or even just send an email.

Speaker #2: Yeah, those are confusing too. But that's not what we're doing here. What we're doing is helping people manage events that are happening at the workplace.

Speaker #1: They're going to have to send an email or a ticket to security and AV and all of these things. And not to mention, this is not just one room in one place.

Speaker #2: They happen every single day among all of our customers, both mid-level and in the enterprise. There are going to be all-hands calls. There are going to be sales kickoffs.

Speaker #1: This is happening potentially around the world in 10 or more places. And they have specific requirements for every location. And so what happens is that the event changes.

Speaker #2: They're going to be training events. And this is really managing the part where you need a room that you can't request yourself. It's not a reservable space.

Speaker #1: Things keep on piling up. And there's somebody there. And when we talk to them, they're literally in tears almost because it's so stressful. We're working with somebody that we're going to launch right now.

Speaker #2: And so, for the people that manage this on the other side—the admins—they're dealing with everything you see on the screen. They're going to get a calendar invite or a request.

Speaker #1: And their quote was, I am the integration layer. Sigh. There is no system that brings it all together, which is great news for us because we have done that now.

Speaker #2: They're going to get an email. They're going to have to open up a ticket in the catering system, or even just send an email.

Speaker #2: They're going to have to send an email or a ticket to Security and AV, and all of these things. And not to mention, this is not just one room in one place.

Speaker #1: And I believe that nobody has done this before because they don't understand corporate workspace like we do. We've got robust rules. We already have the user interface.

Speaker #2: This is happening potentially around the world in ten or more places. And they have specific requirements for every location. So what happens is that the event changes.

Speaker #1: We've already got the integration. So we are so far ahead of that. And so what we leave people with in this current state is high risk.

Speaker #1: You've got things that have to happen on time. It's like a wedding, right? There has to be food. There has to be a room.

Speaker #2: Things keep on piling up, and there's somebody there. When we talk to them, they're literally in tears almost because it's so stressful. We're working with somebody that we're going to launch right now.

Speaker #1: There's executives involved. There's maybe external customers. So it's really high stakes, high risk stuff. So what we've done to answer that is we've got it all into one workflow.

Speaker #2: And their quote was, "I am the integration layer. Sigh." There is no system that brings it all together, which is great news for us because we have done that now.

Speaker #1: This is all one orchestration. You start with the user requesting everything they need. They can see what's available. They can request what they want in terms of space, catering, AV.

Speaker #2: And I believe that nobody has done this before because they don't understand corporate workspace like we do. We've got robust rules. We already have the user interface.

Speaker #1: It doesn't mean they're going to get it. It has to be approved. So there's an approval workflow, which is the real key here. It's going to send automatic workflows for approval to the various departments that need to approve it.

Speaker #2: We've already got the integration, so we are so far ahead of that. And so what we leave people with in this current state is high risk.

Speaker #2: You've got things that have to happen on time. It's like a wedding, right? There has to be food; there has to be a room.

Speaker #1: And at the end of the day, you've got one system here that's wrapping all that up. So this is super exciting for us because it's an add-on, not just for our customers we have today.

Speaker #2: There are executives involved. There may be external customers, so it's really high-stakes, high-risk stuff. What we've done to address that is we've got it all into one workflow.

Speaker #1: We're going to market with this as a standalone as well. And we've got campaigns that are starting right now, full demand campaigns. We're also leveraging the engine rooms platform that will help us even further promote this.

Speaker #2: This is all one orchestration. You start with the user requesting everything they need. They can see what's available. They can request what they want in terms of space, catering, or AV.

Speaker #1: So I'll talk more about that in just a second. But as you can tell, I'm very excited. And so if there's a slide here or a message that I want you to take away today, it's really this.

Speaker #2: It doesn't mean they're going to get it. It has to be approved. So there's an approval workflow, which is the real key here. It's going to send automatic workflows for approval to the various departments that need to approve it.

Speaker #1: It's the enterprise market for us has proven our model. It's proven our technology. We know we have product market fit. We know we can operate in very complex environments.

Speaker #2: And at the end of the day, you’ve got one system here that’s wrapping all that up. So this is super exciting for us because it’s an add-on, not just for our customers we have today.

Speaker #1: It's now the mid-market that scales. And I want to be really clear about something. We are not leaving the enterprise market. We've got great customers.

Speaker #2: We're going to market with this as a standalone as well. And we've got campaigns that are starting right now—full demand campaigns. We're also leveraging the Engine Room's platform that will help us even further promote this.

Speaker #1: And we're going to continue I'm sure we're the best in the world when they go looking for it. But as I described, it's a grueling process.

Speaker #1: It takes a while. But when you win, you win big. So what we've done here is we're taking everything we've learned in enterprise. We've productized it.

Speaker #2: So I'll talk more about that in just a second. But as you can tell, I'm very excited. And so if there's a slide here or a message that I want you to take away today, it's really this:

Speaker #1: And we're going to now take this to market and deploy it in a rapid provisioning. OK, so this means that the connectors as Kerem described, they're preconfigured.

Speaker #2: It's the enterprise market, for us, that has proven our model. It's proven our technology. We know we have product-market fit. We know we can operate in very complex environments.

Speaker #1: They don't have to be built out. They're going to be dropped plug and play, basically. And then we have opportunities we've never had before.

Speaker #1: This is truly different. We have engine rooms. As their customer base. So we've got they've got growth-minded customers that this would apply to as well, the products that we're talking about.

Speaker #2: It's now the mid-market—the scales. And I want to be really clear about something: we are not leaving the enterprise market. We've got great customers.

Speaker #2: And we're going to continue. I'm sure we're the best in the world when they go looking for it. But as I described, it's a grueling process.

Speaker #1: Not only that, we've got their technology to super promote from a lead generation perspective that we've never had before. We've got resellers that are signed up and ready to go for this.

Speaker #2: It takes a while, but when you win, you win big. So what we've done here is we're taking everything we've learned in enterprise, and we've productized it.

Speaker #1: And we've got our marketplace partners where somebody's going to be able to go into the marketplace where they're already buying software, AWS or Google, buy it, start using it.

Speaker #2: And we're going to now take this to market and deploy it in rapid provisioning. OK, so this means that the connectors, as Kerem described, they're preconfigured.

Speaker #1: So the time to value is extremely fast, which is, of course, is going to result in scale. So an important point about this is that we're not just recreating what we did in the enterprise and doing it down market.

Speaker #2: They don't have to be built out. They're going to be dropped in—plug and play, basically. And then we have opportunities we've never had before.

Speaker #1: That would mean hey, we're just doing smaller deals and more of them. And the same hard way. It's not that. We have productized what we're doing.

Speaker #2: This is truly different. We have engine rooms as their customer base, so they've got growth-minded customers that this would apply to as well, the products that we're talking about.

Speaker #1: We can do it fast. We can do it easy. And that's what's going to allow us to scale up. OK, so what I wake up and think about every day, here's our operating principles.

Speaker #2: Not only that, we've got their technology to super-promote from a lead generation perspective that we've never had before. We've got resellers that are signed up and ready to go for this.

Speaker #1: And the same goes for Adam, who's running Australia. We now have one TNL. We've got the same set of metrics for the board and for all the US shareholders.

Speaker #2: And we've got our marketplace partners, where somebody's going to be able to go into the marketplace where they're already buying software—AWS or Google—buy it, start using it.

Speaker #1: EBITDA, growth, bookings, revenue, growth, scale. And the way we do that and the way that we're going to do that in our business here is we've got to deploy.

Speaker #2: So the time to value is extremely fast, which, of course, is going to result in scale. An important point about this is that we're not just recreating what we did in the enterprise and doing it down market.

Speaker #2: That would mean, hey, we're just doing smaller deals and more of them, and the same hard way. It's not that. We have productized what we're doing.

Speaker #1: So we are mid-flight. We've got huge projects going. They're getting deployed flawlessly. We're getting them out there. That's the number one goal. All those customers I mentioned to you, they're going to get out there.

Speaker #2: We can do it fast. We can do it easily. And that's what's going to allow us to scale up. OK, so what I wake up and think about every day—here are our operating principles.

Speaker #1: And what does that mean? That means we're going to start generating recurring revenue as soon as they're out and being used. We've got adoption.

Speaker #1: So I mentioned to you events. Literally, everybody we talk to, they have this problem. And it's a burning problem. So we believe that we're going to do a lot of upsells, whether existing customers.

Speaker #2: And the same goes for Adam, who's running Australia. We now have one P&L. We've got the same set of metrics for the board and for all the U.S. shareholders.

Speaker #1: We're also going to do, as I mentioned, a standalone product. But some of our customers, most of our customers are still on our previous platform.

Speaker #2: EBITDA, growth, bookings, revenue, growth, scale. And the way we do that, and the way that we're going to do that in our business here, is we've got to deploy.

Speaker #1: And it represents a great opportunity to enrich their experience, but also for upsells and add-ons. So things like Agentic AI and other modules like the events and other things that may not have today those represent opportunities to increase revenue with the base.

Speaker #2: So, we are mid-flight. We've got huge projects going. They're getting deployed flawlessly. We're getting them out there. That's the number one goal. All those customers I mentioned to you, they're going to get out there.

Speaker #2: And what does that mean? That means we're going to start generating recurring revenue as soon as they're out and being used. We've got adoption.

Speaker #1: Then we're talking about major expansion. This is what I get really excited about. We have everything I just talked about. We've got pipeline deals.

Speaker #2: So I mentioned to you events. Literally, everybody we talk to, they have this problem, and it's a burning problem. So, we believe that we're going to do a lot of upsells, whether existing customers.

Speaker #1: We're enterprise. We've got add-ons. But we've got this new productivity tool at the employee level that will go up and down market. This is something that's going to apply the product beat for enterprise customers.

Speaker #2: We're also going to do, as I mentioned, a standalone product. But some of our customers—most of our customers—are still on our previous platform.

Speaker #1: It's going to apply for mid-market. It's going to help people do their jobs better and teams deliver which is going to really result in expansion for us.

Speaker #2: And it represents a great opportunity to enrich their experience, but also for upsells and add-ons. So things like Agentic AI and other modules, like the Events and other things that may not have today, those represent opportunities to increase revenue with the base.

Speaker #1: So all of that combined by Q4, we're going to have a new cohort of revenue. These are customers that we don't have today. They will be generating new recurring revenue.

Speaker #1: And that's the goal here. All right, so to wrap things up for me, two engine has just become one. And I think that's really what Kerem has been talking about today is that we are one company.

Speaker #2: Then we're talking about major expansion. This is what I get really excited about. We have everything I just talked about. We've got pipeline deals.

Speaker #2: We're enterprise, we've got add-ons, but we've got this new productivity tool at the employee level that will go up and down market. This is something that's going to apply the product beat for enterprise customers.

Speaker #1: And we are way better for it. So what we've learned in the enterprise, we're now taking into the mid-market. I mentioned to you that engine room already has customers today that are going to be great candidates for us.

Speaker #2: It's going to apply for mid-market. It's going to help people do their jobs better, and teams deliver, which is going to really result in expansion for us.

Speaker #1: We're going to use their tools to grow. And really, the whole second part of the flywheel here is engine room. And I think a really important message we also want to get through to everybody today is that we now have a common backbone.

Speaker #2: So all of that combined, by Q4 we're going to have a new cohort of revenue. These are customers that we don't have today. They will be generating new recurring revenue.

Speaker #1: So the sky Agentic AI platform, although servicing very different use cases and workflows, we are leveraging a low-cost model through Bond and Cortex that allow us to deliver maximum value to our customers.

Speaker #2: And that's the goal here. All right, so to wrap things up for me, two engines have just become one. And I think that's really what Kerem has been talking about today—that we are one company.

Speaker #2: And we are way better for it. So, what we've learned in the enterprise, we are now taking into the mid-market. I mentioned to you that Engine Room already has customers today that are going to be great candidates for us.

Speaker #1: And so I'm going to turn it over to Adam here in just a second. And this is great news for us as a company.

Speaker #1: It's such a lift because Adam already has scale. He's already got profitable growth. And he's got a great product. So I'm excited to turn it over to Adam.

Speaker #2: We're going to use their tools to grow. And really, the whole second part—and I think a really important message we also want to get through to everybody today—is that we now have a common backbone.

Speaker #1: Adam?

Speaker #2: Thanks, Chris. I appreciate that. And a big hello from Australia to everyone joining us from around the world. My name is Adam Lorry. And I'm the co-founder of Engine Room.

Speaker #2: So, the Sky Agentic AI platform, although servicing very different use cases and workflows, leverages a low-cost model through Bond and Cortex that allows us to deliver maximum value to our customers.

Speaker #2: And now general manager of Sky's Australian operations. Speaking personally, Engine Room has been such a major part of my life from 13 years. So I'm really excited today to have the opportunity to introduce it to all Sky shareholders and people on this call for the first time.

Speaker #2: And so, I'm going to turn it over to Adam here in just a second. This is great news for us as a company.

Speaker #2: It's such a lift because Adam already has scale. He's already got profitable growth, and he's got a great product. So I'm excited to turn it over to Adam.

Speaker #2: So the purpose of today I want to bring you into the world of Engine Room, show you what we've built, why it works, give you an understanding of what Sky has acquired, and most importantly, to showcase the opportunity we have to build something collectively bigger together.

Speaker #2: Adam?

Speaker #3: Thanks, Chris, I appreciate that. And a big hello from Australia to everyone joining us from around the world. My name is Adam Lorry, and I'm the co-founder of Engine Room.

Speaker #3: And now, General Manager of Sky's Australian operations. Speaking personally, Engine Room has been such a major part of my life for 13 years, so I'm really excited today to have the opportunity to introduce it to all Sky shareholders and people on this call for the first time.

Speaker #2: OK, so what's our purpose? And what are we here to achieve as a business? We use data digital and AI effectively to enable smarter decisions and unlock greater growth potential for our clients.

Speaker #2: That's what we do. We are revenue generators, profitable revenue generators for our clients. And that's what I utilize what we provide. We're an established business.

Speaker #3: So, the purpose of today—I want to bring you into the world of Engine Room, show you what we've built, why it works, and give you an understanding of what Sky has acquired.

Speaker #2: And we have a very strong proven track record. We're Australian based. We serve businesses across the Australasian marketplace at this point in time. We have a 30-year history.

Speaker #3: And most importantly, to showcase the opportunity we have to build something collectively bigger together. Okay, so what's our purpose? And what are we here to achieve as a business?

Speaker #2: We're first established back in 2013. We're a multi-award winning across multiple facets, including performance, innovation, and most importantly, for any business, our people. What we do as a business, we're fully integrated growth marketing solutions designed to capture high-intent demand and drive sustainable profitable growth for our clients.

Speaker #3: We use data, digital, and AI effectively to enable smarter decisions and unlock greater growth potential for our clients. That's what we do. We are revenue generators—profitable revenue generators—for our clients.

Speaker #3: And that's why I utilize what we provide. We're an established business, and we have a very strong, proven track record. We're Australian-based, and we serve businesses across the Australasian marketplace at this point in time.

Speaker #2: So we have three major divisions. We have our MarTech platform, which we'll go through shortly. Fractional CMO and then marketing as a service. What problem do we solve?

Speaker #2: And everything that we do always comes back to the genesis of what's our purpose and what problem are we solving for a business? So why do they want to spend with days has difficulty building a cost-effective and scalable customer acquisition engine.

Speaker #3: We have a 30-year history. We were first established back in 2013. We're multi-award-winning across multiple facets, including performance, innovation, and most importantly for any business, our people.

Speaker #3: What we do as a business—we're fully integrated growth marketing solutions, designed to capture high-intent demand and drive sustainable, profitable growth for our clients.

Speaker #2: And without customers, businesses obviously struggle to grow. They have difficulty measuring marketing ROI and demonstrating commercial impact. They have disconnected business customer and digital data that don't communicate and don't speak.

Speaker #3: So we have three major divisions. We have our MarTech platform, which we'll go through shortly, our Fractional CMO, and then Marketing as a Service. What problem do we solve?

Speaker #2: And they have a failure to convert knowledge data and AI into a commercial event. And that's the problem that we solve. We create growth marketing solutions that transform these strategies into measurable, scalable, and profitable outcomes.

Speaker #3: And everything that we do always comes back to the genesis of what's our purpose and what problem are we solving for a business. So, why do they want to spend with us?

Speaker #2: We build cost-effective acquisition engines for our clients. We deliver clear, measurable ROI and commercial performance insights. We uniform data strategy and execution into a single source of truth.

Speaker #3: So, a business these days has difficulty building a cost-effective and scalable customer acquisition engine. And without customers, businesses obviously struggle with growth. They have difficulty measuring marketing ROI and demonstrating commercial impact.

Speaker #2: And we transform the knowledge and data into a sustained commercial and competitive advantage for them. The key is also what we do. And just as importantly, what we don't do.

Speaker #3: They have disconnected business customer and digital data that don't communicate and don't speak. And they have a failure to convert knowledge, data, and AI into a commercial advantage.

Speaker #2: So in the world of digital execution, there's two primary markets. There's awareness. And there's intent. Awareness is obviously when I am not aware or I'm not thinking about making a transactional purchase in the transaction.

Speaker #3: And that's the problem that we solve. We create growth marketing solutions that transform these strategies into measurable, scalable, and profitable outcomes. We build cost-effective acquisition engines for our clients.

Speaker #2: But I might be induced by a commercial or something to think about it. We don't focus on that market. We focus on the intent market for our clients.

Speaker #3: We deliver clear, measurable ROI and commercial performance insights. We unify data strategy and execution into a single source of truth. And we transform the knowledge and data into a sustained commercial and competitive advantage for them.

Speaker #2: And those are people who are actively already out there looking for a product and service that our client provides. And we do that because that's the most profitable part of a market that a customer can access.

Speaker #3: The key is also what we do, and just as importantly, what we don't do. So, in the world of digital execution, there are two primary markets.

Speaker #2: They're high-intent customers. They're not necessarily discount orientated. And they're high converting. And that's the market that we focus on for our customers. It's also very measurable because it's towards the end of their journey.

Speaker #3: There's awareness, and there's intent. Awareness is obviously when I am not aware or I'm not thinking about making a transaction or purchasing. But I might be induced by a commercial or something to think about it.

Speaker #2: Why do customers choose us? We have proven results in delivering for over 13 years now. We have cutting-edge technology that powers smarter data-driven decisions.

Speaker #3: We don't focus on that market. We focus on the intent market for our clients, and those are people who are already actively out there looking for a product or service that our client provides.

Speaker #2: We have solutions that achieve substantial and measurable ROI. We have a fully integrated end-to-end solution profile. And we have unmatched in-house expertise and support.

Speaker #3: And we do that because that's the most profitable part of a market that the customer can access. They're high-intent customers. They're not necessarily discount-orientated.

Speaker #2: So if we look at the MarTech platform that I touched on personally, which forms the foundation of everything that we do and is so critical to our success, so our technology is designed to empower marketers, owners, and advisors to make data-driven decisions that optimize growth and drive success.

Speaker #3: And they're high-converting, and that's the market that we focus on for our customers. It's also very measurable because it's towards the end of their journey.

Speaker #3: Why do customers choose us? We have proven results in delivering for over 13 years now. We have cutting-edge technology that powers smarter, data-driven decisions.

Speaker #2: We effectively have three main parts to our platform. We have strategize, analyze, and optimize. And they're all meant to be interlinked to form solution.

Speaker #3: We have solutions that achieve substantial and measurable ROI. We offer a fully integrated, end-to-end solution profile. And we have unmatched in-house expertise and support.

Speaker #2: So the purpose of strategize, where are we going? What's the purpose of what we're doing here? So we have context, set the direction, define objectives.

Speaker #3: So, if we look at the MarTech platform that I touched on personally, which forms the foundation of everything that we do and is so critical to our success.

Speaker #2: Analyze, how are we performing? Measure and understand performance. Maximize opportunities, identify risks. And then optimize. What should we do next? What's the actions that will drive improvement and gain me a commercial advantage?

Speaker #3: So, our technology is designed to empower marketers, owners, and advisors to make data-driven decisions that optimize growth and drive success. We effectively have three main parts to our platform.

Speaker #2: And those three parts are all important because ultimately, if you don't have all three parts, then you're going to be missing out on a key part of growth.

Speaker #3: We have strategize, analyze, and optimize. And they're all meant to be interlinked to form a cohesive end-to-end solution. So, the purpose of strategize—where are we going?

Speaker #2: Each module that we then build within the platform has a specific application within those sectors. And we have a whole host of different modules we won't go into detail today.

Speaker #3: What's the purpose of what we're doing here? So, we have context, set the direction, define objectives. Analyze—how are we performing? Measure and understand performance.

Speaker #2: But they have very specific applications that we can call and draw on as required when we're engaging with our clients or the clients are working through the platform.

Speaker #3: Maximize opportunities, identify risks, and then optimize. What should we do next? What are the actions that will drive improvement and gain me a commercial advantage?

Speaker #2: So what's important to understand about how we utilize AI and how our technology gains a commercial advantage? LLMs understand language. We all know that.

Speaker #3: And those three parts are all important because, ultimately, if you don't have all three parts, then you're going to be missing out on a key part of growth.

Speaker #2: The key with the engineering platform is it teaches AI to understand the business. And that's the key difference. And to do that, we really have to base our AI in a strong foundation.

Speaker #3: Each module that we then build within the platform has a specific application within those sectors, and we have a whole host of different modules.

Speaker #2: So what we do is we bring in core parts of data of a business. We bring in their business aspects. So what their goals and objectives are.

Speaker #3: We won't go into detail today, but they have very specific applications that we can call on and draw from as required when we're engaging with our clients or when the clients are working through the platform.

Speaker #2: What their brand identity is. We bring in their customers' understand their target market, understand how they're trying to engage with them, understand their commercial advantages.

Speaker #3: So, what's important to understand about how we utilize AI, and how our technology gains a commercial advantage? LLMs understand language—we all know that.

Speaker #2: We bring in information in relation to the competitors. What the market's doing. And then we bring in, obviously, the information in relation to their individual performance.

Speaker #3: The key with the engineering platform is it teaches AI to understand the business. And that's the key difference. To do that, we really have to base our AI on a strong foundation.

Speaker #2: That forms that framework for us. And then when we are driving through AI, it gives us the foundation to effectively produce stronger outcomes and stronger recommendations.

Speaker #3: So what we do is we bring in core parts of data from a business. We bring in their business aspects—so what their goals and objectives are.

Speaker #2: And you would know that when you're using a lot of tools in the marketplace that maybe use AI, very generic in nature. And they'll basically say, these two businesses are in the same sector, want the same things.

Speaker #3: What their brand identity is. We bring in their customers, understand their target market, understand how they're trying to engage with them, and understand their commercial advantages.

Speaker #2: But they really don't because they're all individual businesses who have different needs, different competitors, different sectors, different profit margins, et cetera. And without that context, it's going to be lower quality insights and lower quality information.

Speaker #3: We bring in information in relation to the competitors, what the market's doing, and then we bring in, obviously, the information in relation to their individual performance.

Speaker #2: Us grounding it in this real core knowledge database enables our customers to gain a significant commercial advantage. The other thing important is that when we're using AI, it's a continuous learning application.

Speaker #3: That forms the framework for us. And then, when we are driving through AI, it gives us the foundation to effectively produce stronger outcomes and stronger recommendations.

Speaker #3: And you would know that when you're using a lot of tools out in the marketplace that maybe use AI, they're very generic in nature. And they'll basically say, these two businesses are in the same sector, want the same things.

Speaker #2: So we store all this data and every month that we're storing this data for our clients, we are improving the functionality in the output of what it can deliver.

Speaker #3: But they really don't, because they're all individual businesses who have different needs, different competitors, different sectors, different profit margins, et cetera. And without that context, it's going to be lower-quality insights and lower-quality information.

Speaker #2: So it's a living, breathing, learning tool that enables us to continuously move forward with our clients. And that's a really important part both the knowledge center and the time aspect to continuously gain that commercial advantage for our clients.

Speaker #3: Us grounding it in this real core knowledge database enables our customers to gain a significant commercial advantage. The other thing that's important is that when we're using AI, it's a continuous learning application.

Speaker #2: And that's where you get back to, ultimately, a prompt and answer versus a knowledge and action. So traditional AI, give it a prompt. And then it'll be like, here's the answer.

Speaker #2: We recommend. And it's a very generic prompt. And it's a generic answer because it's done in the context of everything and everyone. Whereas an engine room, we have that specific knowledge.

Speaker #3: So, we store all this data, and every month that we're storing this data for our clients, we are improving the functionality and the output of what it can deliver.

Speaker #2: And we have that specific reasoning from learning. And that enables us to do a very high quality action specific to that client's needs. So today, we're going to show you an example of the platform, which is going to go through a few modules.

Speaker #3: So, it's a living, breathing, learning tool that enables us to continuously move forward with our clients. And that's a really important part—both the Knowledge Center and the time aspect—to continuously gain that commercial advantage for our clients.

Speaker #2: The client I'm going to show you is a smaller client. But they've kindly enabled us to showcase their data. But it doesn't matter where it's a small or a larger client.

Speaker #3: And that's where you get back to, ultimately, a prompt and answer versus a knowledge and action. So traditional AI, give it a prompt. And then it'll be like, here's the answer.

Speaker #2: But the same principles apply. And I'm going to give you an example into just some of the modules in how we apply them and how we discuss them when we talk with our client.

Speaker #3: That's what we recommend. And it's a very generic prompt, and it's a generic answer because it's done in the context of everything and everyone. Whereas in an engine room, we have that specific knowledge.

Speaker #2: So David, if you'd like to press play. Thanks.

Speaker #3: And we have that specific reasoning from learning, and that enables us to do a very high-quality action specific to that client's needs. So today, we're going to show you an example of the platform, which is going to go through a few modules.

Speaker #3: Hello and welcome to Engine Room. Today, I'll show you how Engine Room works in practice through a real customer example. Showcasing just a few of the platform features we've used to help you form this strategy, optimize performance, and ultimately drive their growth.

Speaker #3: The client I'm going to show you is a smaller client, but they've kindly enabled us to showcase their data. But it doesn't matter whether it's a small or a larger client.

Speaker #3: While this is a smaller customer who's agreed to share their data, the same principles apply across our entire customer base, including significantly larger businesses.

Speaker #3: But the same principles apply. And I'm going to give you an example from just some of the modules, in how we apply them and how we discuss them when we talk with our client.

Speaker #3: So ultimately, where would we start? We would start with how the business is performing because ultimately, that's what we're here to help them achieve.

Speaker #3: So, David, if you'd like to press play. Thanks. Today, I'll show you how our engine works in practice through a real customer, for example, showcasing just a few of the platform features we've used to help inform their strategy, optimize performance, and ultimately drive their growth.

Speaker #3: And we can look at this particular customer. He came on board back in January 2025 with our generating a small amount of revenue, about $64,000 a month.

Speaker #3: And the majority of it was from existing customers and a smaller proportion from new. And we can see over the course of the last year and a half that they've grown significantly relative to their starting size.

Speaker #3: About four and a half times in revenue. And the majority of that growth has come from their new customer revenue. So they're all good signals.

Speaker #3: While this is a smaller customer who has agreed to share their data, the same principles apply across our entire customer base, including significantly larger businesses.

Speaker #3: But then if we look back and what does that ultimately mean in the context of what the business is seeking to achieve? We can have a look at the plans that we put in originally prior to the start of the year.

Speaker #3: So, ultimately, where would we start? We would start with how the business is performing, because ultimately, that's what we're here to help them achieve.

Speaker #3: And they're looking to achieve about 1.6 million dollars in revenue. And what that translated through to a new customers and ultimately conversions and their priorities and challenges.

Speaker #3: And we can look at this particular customer. He came on board back in January 2025, generating a small amount of revenue, about $64,000 a month.

Speaker #3: And the majority of it was from existing customers, with a smaller proportion from new ones. We can see, over the course of the last year and a half, that they've grown significantly relative to their starting size.

Speaker #3: And then now that we've finished the financial year, we can look back and say, well, what have we achieved? What worked? What could be optimized?

Speaker #3: What risk could be minimized? And we can see that for all the major metrics being revenue, yield, and customers, they outperform the original targets.

Speaker #3: About four and a half times in revenue. And the majority of that growth has come from their new customer revenue, so they're all good signals.

Speaker #3: And if we drill down into more micro information, we can see different elements and then ultimately go, how do we maximize these areas? Other things that we look at is things like how are they going relative to their competitors?

Speaker #3: But then, if we look back, what does that ultimately mean in the context of what the business is seeking to achieve? We can have a look at the plans that we put in originally, prior to the start of the year.

Speaker #3: And they're looking to achieve about $1.6 million in revenue. And what that translates to is new customers and, ultimately, conversions—and their priorities and challenges.

Speaker #3: So if we look at the last financial year, and ultimately one of the things they're looking to do is gain market share versus their competitors.

Speaker #3: And that's our particular customer. We can see that they're growing. And we can look to identify and go, well, who are they actually capturing market share from?

Speaker #3: And now that we've finished the financial year, we can look back and say, well, what have we achieved? What worked? What could be optimized?

Speaker #3: That would be an important consideration. Other things we'll be discussing with them is what's happening in relation to their leads. So if we can drill down into an individual lead, we can see for this particular customer, which aspects are they looking at and inquiring about from their business?

Speaker #3: What risk could be minimized? And we can see that for all the major metrics—revenue, yield, and customers—they outperformed the original targets.

Speaker #3: And if we drill down into more micro information, we can see different elements and then ultimately go, how do we maximize these areas? Other things that we look at are things like how are they going relative to their competitors?

Speaker #3: And which parts of their websites are they consuming to ultimately make a decision to contact them? And then from a macro point of view, we can look at their new customer opportunities.

Speaker #3: Once again, if we have a look at last financial year, and we can drill down and see that things like okay, so what was the main thing they're looking for?

Speaker #3: So if we look at the last financial year, ultimately one of the things they're looking to do is gain market share versus their competitors.

Speaker #3: Or what business segments were they inquiring about? All these considerations when deciding next phase of the program. We'll also be looking at things like attribution, and so once again, if we look at not the last month, but the last financial year, we can look and go, okay, well, that was their overall marketing investment.

Speaker #3: And that's our particular customer. We can see that they're growing, and we can look to identify and go, well, who are they actually capturing market share from?

Speaker #3: That would be an important consideration. Other things we'll be discussing with them are what's happening in relation to their leads. So, if we can drill down into an individual lead, we can see, for this particular customer, which aspects they are looking at and inquiring about from their business.

Speaker #3: And that was the attributed revenue. But then how did that break down for first versus secondary transactions? By period in time, ultimately all the way down to channel.

Speaker #3: And which parts of their websites are they consuming to ultimately make a decision to contact them? And then, from a macro point of view, we can look at their new customer opportunities.

Speaker #3: We can look at individual customers. For example, the conversion that they journeyed they took or their invoice that they purchased with. Also things like which campaigns were performing better in Google Ads, et cetera, relative to revenue and spend.

Speaker #3: Once again, if we have a look at last financial year, we can drill down and see things like, okay, what was the main thing they were looking for?

Speaker #3: Or what business segments were they inquiring about? All these considerations come into play when deciding the next phase of the program. We'll also be looking at things like attribution.

Speaker #3: So there's just a sample of the things that we'd look at. There's a whole plethora of information on the left-hand side that we could drill down and look at.

Speaker #3: But ultimately, we would determine that on a case-by-case basis. But there's just an insight. Thank you.

Speaker #3: And so once again, if we look at not the last month, but the last financial year, we can look and go, okay, well, that was their overall marketing investment.

Speaker #3: And that was the attributed revenue. But then, how did that break down for first versus secondary transactions, by period in time—ultimately all the way down to channel?

Speaker #3: We can look at individual customers—for example, the conversion that they journeyed through, or the invoice that they purchased with. Also, things like which campaigns were performing better in Google Ads, et cetera, relative to revenue and spend.

Speaker #1: I hope everyone enjoyed that. Okay. So why Engine Room and Sky? So CXAI's oscillation we are looking to be CXAI's oscillation growth engine. Karam already touched on that before.

Speaker #3: So that's just a sample of the things that we look at. There's a whole plethora of information on the left-hand side that we could drill down into and look at.

Speaker #1: We are a business that has grown substantially year on year, that has generated ongoing growth strategies. We target customers who are in that 5 to 500 historical customer range.

Speaker #3: But ultimately, we would determine that on a case-by-case basis. But that's just an insight. Thank you.

Speaker #1: Average client yield is around about 200,000 dollars per annum. We have 93% recurring revenue and average client extends beyond four years in life. Our customers across are diversified industry sectors.

Speaker #2: I hope everyone enjoyed that. Okay, so why Engine Room and Sky? So, CXAI's oscillation—we are looking to be CXAI's oscillation growth engine. Khurram already touched on that before.

Speaker #1: Professional services, home services, manufacturing, industrial, et cetera. So we have a strong diversified mix which is a great foundation for the next stage of our growth.

Speaker #2: We are a business that has grown substantially year over year and has developed ongoing growth strategies. We target customers who are in the 5 to 500 historical customer range.

Speaker #1: We have a proven track record of scalable growth year on year. As you can see over the last five years, we have consistently grown.

Speaker #1: And that's profitable growth with consistently move forward with. Importantly, for any company we have a proven team and we have leadership who are staying on board.

Speaker #2: Average client yield is around $200,000 per annum. We have 93% recurring revenue, and an average client extends beyond four years in life. Our customers are across diversified industry sectors.

Speaker #1: We have an award-winning culture which has been recognized I think for the last five years and experienced leadership. And we have a very strong specialist capability or capacity that who are being retained.

Speaker #2: Professional services, home services, manufacturing, industrial, et cetera. So we have a strong, diversified mix, which is a great foundation for the next stage of our growth.

Speaker #1: Across technology, AI, data, engineering, and growth marketing expertise. What does that mean for the future? Well, there is enormous growth opportunity even in the oscillation marketplace.

Speaker #2: We have a proven track record of scalable growth year on year. As you can see, over the last five years, we have consistently grown.

Speaker #2: And that's profitable growth we've consistently moved forward with. Importantly, for any company, we have a proven team and leadership who are staying on board.

Speaker #1: We are in a sector we are fortunate to be in a sector that has high growth in all capacity, whether it be MarTech, the fractional CMO, or marketing as a service.

Speaker #2: We have an award-winning culture, which has been recognized, I think, for the last five years, and experienced leadership. And we have a very strong specialist capability or capacity who are being retained.

Speaker #1: And even in the context of Australia, even though we turnover, $8 million. The context is that the growth opportunities in Australia are so, so significant.

Speaker #1: And that's one of the things that is exciting about CXAI in Australia coming on board is that it will enable us to hopefully unlock so much of that growth opportunity that we know is available.

Speaker #2: Across technology, AI, data, engineering, and growth marketing expertise, what does that mean for the future? Well, there is enormous growth opportunity, even in the oscillation marketplace.

Speaker #2: We are in a sector—we are fortunate to be in a sector—that has high growth in all capacities, whether it be MarTech, the fractional CMO, or marketing as a service.

Speaker #1: So what's the next steps from here on the pathway forward? So accelerating Engine Room with Sky. So combining Engine Room's expertise and customer relationships with Sky's agentic AI capabilities.

Speaker #2: And even in the context of Australia, even though we turn over $8 million, the context is that the growth opportunities in Australia are so, so significant.

Speaker #1: So we can look to we already do a semblance of AI, but we know that Sky has strong agentic capabilities. And we have the capability or capacity to look where that can be integrated and improve what we do as a business.

Speaker #2: And that's one of the things that is exciting about CXAI in Australia coming on board—it will enable us to hopefully unlock so much of that growth opportunity that we know is available.

Speaker #1: We'll be looking to accelerate our product development. Once again, leveraging off Sky's expertise and expand our data and intelligence capabilities. So to that end, Engine Room business knowledge plus Sky agentic AI, we're looking to improve the intelligence, the reasoning, and the action outcomes.

Speaker #2: So, what's the next step from here and the pathway forward? So, accelerating Engine Room with Sky—combining Engine Room's expertise and customer relationships with Sky as agentic AI capabilities.

Speaker #1: To give you some context from a development architecture, so at the moment we have done a lot in the data source of truth and the business knowledge, which I touched on before.

Speaker #2: So we can look to—we already do a semblance of AI, but we know that Sky has strong agentic capabilities. And we have the capability or capacity to look at where that can be integrated and improved in what we do as a business.

Speaker #1: And we've started with the reasoning and the decision engine. What we look for in the future roadmap is to strengthen the reasoning and decision intelligence.

Speaker #2: We'll be looking to accelerate our product development, once again leveraging Sky's expertise and expanding our data and intelligence capabilities. So to that end, with engine room business knowledge plus Sky agentic AI, we're looking to improve the intelligence, the reasoning, and the action outcomes.

Speaker #1: But then also look at taking the next step, and this is where Sky's capabilities come into play, is with agents and autonomous business execution.

Speaker #1: Which we see as a big opportunity for the next steps forward. So the commercial opportunities. We are strategically positioned to capitalize on key market opportunities that will drive future growth and value creation.

Speaker #2: To give you some context from a development architecture: at the moment, we have done a lot in the data source of truth and the business knowledge, which I touched on before.

Speaker #1: We look to expand into new verticals. Growth through strategic partnerships and channel expansion. Technology innovation to increase customer value, retention, and lifetime value. Look to use AI to drive efficiencies and scalability and profitability.

Speaker #2: And we've started with the reasoning and the decision engine. What we look for in the future roadmap is to strengthen the reasoning and decision intelligence.

Speaker #1: And strengthen the competitive differentiation between us and other people out there in the industry. But as I touched on before, the capacity for growth is just enormous.

Speaker #2: But then also look at taking the next step, and this is where Sky's capabilities come into play—which is with agents and autonomous business execution.

Speaker #1: As long as we execute to that high level. So I just want to say thank you. Lovely to meet everyone today. A lovely to introduce the Engine Room story.

Speaker #2: Which we see as a big opportunity for the next steps forward. So, the commercial opportunities—we are strategically positioned to capitalize on key market opportunities that will drive future growth and value creation.

Speaker #2: We look to expand into new verticals—growth through strategic partnerships and channel expansion. Technology innovation to increase customer value, retention, and lifetime value. We look to use AI to drive efficiencies, scalability, and profitability.

Speaker #1: We're very excited about it. And we're very excited about the next steps. And I'll hand it over next to Zoe, who we're going to be doing a fireside chat with.

Speaker #2: And strengthen the competitive differentiation between us and other companies out there in the industry. But as I touched on before, the capacity for growth is just enormous.

Speaker #2: Hey everyone. So my name is Zoe Chen. I'm a workplace strategist at Felton and Company. I spend most of my time inside companies while they're in the middle of changing how they work, not the strategy deck version.

Speaker #2: As long as we execute at that high level. So I just want to say thank you. Lovely to meet everyone today—lovely to introduce the Engine Room story.

Speaker #2: The actual version. So it's the part where somebody has to tell 300 people that they're losing their assigned seats and will be sharing desks in the future.

Speaker #2: What's really interesting in this particular moment is that everybody in the building is talking about AI. Even when the project is about building out the physical space.

Speaker #2: We're very excited about it, and we're very excited about the next steps. I'll hand it over next to Zoe, who we're going to be doing a fireside chat with.

Speaker #2: So I want to give you three things, I think, are true right now. They're not predictions. They're just what I keep running into. And then I'll invite Chris Adam and Corinne to ask me some questions.

Speaker #3: Hi, everyone. So, my name is Zoe Chen. I'm a workplace strategist at Felton and Company. I spend most of my time inside companies while they're in the middle of changing how they work—not the strategy deck version.

Speaker #2: So the first one. Here's what I would have told you 10 years ago and I would have been right. Automation starts at the bottom and works its way up.

Speaker #2: That's the pattern. The assembly line, the ATM, self checkout, the scanners in a warehouse. Machines were good at doing the same physical thing over and over and bad at basically everything else.

Speaker #3: The actual version—so it's the part where somebody has to tell 300 people that they're losing their assigned seats and will be sharing desks in the future.

Speaker #3: What's really interesting in this particular moment is that everybody in the building is talking about AI, even when the project is about building out the physical space.

Speaker #2: So the safe advice was get more education, get further from the repetitive stuff, and you'll stay ahead of it. That was the real deal for about 40 years.

Speaker #3: So, I want to give you three things I think are true right now. They're not predictions; they're just what I keep running into. And then I'll invite Chris, Adam, and Corinne to ask me some questions.

Speaker #2: And then this technology showed up and completely ignored it. Because it turns out the things that took us the longest to learn, writing, analyzing, summarizing, coding, those are cheap ones to replicate.

Speaker #3: So, the first one: Here's what I would have told you 10 years ago—and I would have been right. Automation starts at the bottom and works its way up. That's the pattern.

Speaker #2: Now, and the thing that a kid can do without thinking, like walking into an unfamiliar room and picking up an oddly shaped object, those are still incredibly difficult.

Speaker #3: The assembly line, the ATM, self-checkout, the scanners in a warehouse—machines were good at doing the same physical thing over and over, and bad at basically everything else.

Speaker #2: And there's good data on this now, not just anecdotes. Anthropic has been publishing something called the Economic Index, where they analyze millions of real conversations with their AI to see what people are actually using it for, mapped against the government's occupational database.

Speaker #3: So the safe advice was: get more education, get further from the repetitive stuff, and you'll stay ahead of it. That was the real deal for about 40 years.

Speaker #2: And what comes out is pretty clear. The heaviest uses clusters emit to high wage occupations. Both very low paying and very high paying jobs show low AI use.

Speaker #3: And then this technology showed up and completely ignored it. Because it turns out that the things that took us the longest to learn—writing, analyzing, summarizing, coding—those are the cheap ones to replicate.

Speaker #2: Because those tend to be the ones involving a lot of manual dexterity. Their example is shampoers and obstetricians, which tells you something about how little these two have in common except that both require hands.

Speaker #3: Now, the things that a kid can do without thinking, like walking into an unfamiliar room and picking up an oddly shaped object—those are still incredibly difficult.

Speaker #2: So it landed on information work. The desk jobs. And it's not creeping in slowly. About half of all jobs have already seen at least a quarter of their tasks touched by AI.

Speaker #3: And there's good data on this now, not just anecdotes. Anthropic has been publishing something called the Economic Index, where they analyze millions of real conversations with their AI to see what people are actually using it for, mapped against the government's occupational database.

Speaker #2: The flip side is that there is a large part of the workforce sitting in a near zero exposure zone. Electricians, plumbers, HVAC technicians, mechanics.

Speaker #3: And what comes out is pretty clear. The heaviest use is clusters in mid to high-wage occupations, while very low-paying and very high-paying jobs show low AI use.

Speaker #2: So if the job requires you to physically be somewhere and put your hands on something, this wave mostly isn't coming for you. But being protected isn't the same as being unconstrained.

Speaker #3: Because those tend to be the ones involving a lot of manual dexterity. There are examples, such as shampooers and obstetricians, which tells you something about how little these two have in common, except that both require hands.

Speaker #2: Think about the three truck pulling company. What's actually stopping that from becoming a 10 truck business? It's not the plumbing. They're great at plumbing.

Speaker #3: So it landed on information work: the desk jobs. And it's not creeping in slowly; about half of all jobs have already seen at least a quarter of their tasks touched by AI.

Speaker #2: It's everything that happens away from the job site. Whether the quote went out the same day or four days later. Whether somebody followed up on the estimate from two weeks ago.

Speaker #2: Whether the reviews are getting answered. Whether there is a next job lined up when this one is done. So there's a whole back office of a small business.

Speaker #3: The flip side is that there is a large part of the workforce sitting in a near-zero exposure zone: electricians, plumbers, HVAC technicians, and mechanics.

Speaker #2: And it's the part that the owner is least equipped for and probably least interested in. And that's the frustrating bits. There's no shortage of software for them.

Speaker #3: So, if the job requires you to physically be somewhere and put your hands on something, this wave mostly isn't coming for you. But being protected isn't the same as being unconstrained.

Speaker #2: There is a tool for the quoting, a tool for the scheduling, a tool for the reviews, a tool for the follow up. But that's the problem.

Speaker #3: Think about the three-truck plumbing company. What's actually stopping that from becoming a 10-truck business? It's not the plumbing. They're great at plumbing.

Speaker #2: Every one of those needs to be set up, connected to others, and babysat by somebody. Nobody started an HVAC business because they wanted to become a CRM administrator.

Speaker #3: It's everything that happens away from the job site—whether the quote went out the same day or four days later, whether somebody followed up on the estimate from two weeks ago.

Speaker #2: So the choice they've been offered for 20 years has basically been stay small or spend your evenings learning the software. And that's what this feels different to me about this wave of tech innovation.

Speaker #3: Whether the reviews are getting answered, whether there is a next job lined up and this one is done. So, there's a whole back office of a small business.

Speaker #3: And it's the part that the owner is least equipped for and probably least interested in, and that's the frustrating bit. There's no shortage of software for them.

Speaker #2: The promise isn't another tool to master. It's the outcome without the operating burden. And if that lands, the small operators really can get a back office that used to require real scale to afford.

Speaker #3: There is a tool for quoting, a tool for scheduling, a tool for reviews, and a tool for follow-up. But that's the problem.

Speaker #2: OK. Second thing. Everyone on this call probably already used personalized intelligence at least three times before breakfast and didn't even notice once. Your phone sorted your emails before you looked at it.

Speaker #3: Every one of those needs to be set up, connected to others, and babysat by somebody. Nobody started an HVAC business because they wanted to become a CRM administrator.

Speaker #2: Your news app put out top three stories that you actually care about on the very top. Your grocery apps already know that you were low on coffee.

Speaker #3: So, the choice they've been offered for 20 years has basically been: stay small, or spend your evenings learning the software. And that's what feels different to me about this wave of tech innovation.

Speaker #2: And your maps app routed you around something before you even knew that it was there. And none of this felt like technology. It just feels like things are working.

Speaker #3: The promise isn't another tool to master. It's the outcome without the operating burden. And if that lands, the small operators really can get a back office that used to require real scale to afford.

Speaker #2: We've gotten completely used to systems that know us. And when you walk into the office, it all kind of stops. Every app is doing its own thing.

Speaker #3: OK. Second thing. Everyone on this call probably already used personalized intelligence at least three times before breakfast and didn't even notice once. Your phone sorted your emails before you looked at it.

Speaker #2: Nothing knows you. Nothing talks to anything else. As Chris said earlier, you are the integration layer. You are the one holding it together. Now, I want to be fair here.

Speaker #3: Your news app puts out the top three stories that you actually care about at the very top. Your grocery apps already know that you are low on coffee.

Speaker #2: AI has already changed a huge amount about how we handle information. Notes, emails, transcripts, catching up on a meeting you missed. That part is real and people feel it every day.

Speaker #3: And your maps app would route you around something before you even knew that it was there. And then none of this felt like technology.

Speaker #2: What it hasn't done yet is meet people where they actually are. In the building, in the physical space. The building doesn't know you're in it.

Speaker #3: It just feels like things are working. We've gotten completely used to systems that know us. And when you walk into the office, it all kind of stops.

Speaker #2: The room booking system doesn't know your whole team came in today. Your calendar doesn't know you're on the other side of campus with eight minutes to get to your next meeting.

Speaker #3: Every app is doing its own thing. Nothing knows you, nothing talks to anything else. As Chris said earlier, you are the integration layer; you are the one holding it together.

Speaker #2: And this is the part I'd push back on when people talk about workplace productivity. The exhausting part of the day usually isn't the heart problem, that you sign up for at your job.

Speaker #3: Now, I want to be fair here. AI has already changed a huge amount about how we handle information: notes, emails, transcripts, catching up on a meeting you missed.

Speaker #2: It's everything around it. Finding a room, doing the time zone math, figuring out who's actually in today, working out where to sit when half of your team is scattered across three floors.

Speaker #3: The part is real, and people feel it every day. What it hasn't done yet is meet people where they actually are—in the building, in the physical space.

Speaker #2: So every one of these takes 15 seconds. And none of them are your job. But you do 40 of them. And by three in the afternoon, you've burned real mental energy on decisions that should have been made for you.

Speaker #3: The building doesn't know you're in it. The room booking system doesn't know your whole team came in today. Your calendar doesn't know you're on the other side of campus with eight minutes to get to your next meeting.

Speaker #2: Think about what GPS actually does for you. It's not that you wanted a better map. You never wanted a map. You wanted to arrive you wanted to stop thinking about the path.

Speaker #3: And this is the part I'd push back on, when people talk about workplace productivity. The exhausting part of the day usually isn't the hard problem that you sign up for at your job.

Speaker #2: And that's what people want out of their workday. Not more tools. But fewer decisions. And none of this is new, really. Work always lags behind life.

Speaker #3: It's everything around it: finding a room, doing the time zone math, figuring out who's actually in today, and working out where to sit when half of your team is scattered across three floors.

Speaker #2: It did with the phones in your pockets. And it did with video calls. It did with every tool that felt normal at home for years, before it felt normal at the office.

Speaker #3: So every one of these takes 15 seconds, and none of them are your job. But you do 40 of them, and by three in the afternoon, you've burned real mental energy on decisions that should have been made for you.

Speaker #2: So people improvise. They find a workaround. They'll use AI on their phones, on tools nobody bought them. Because it makes their workday a little better.

Speaker #3: Think about what GPS actually does for you. It's not that you wanted a better map. You never wanted a map. You wanted to arrive. You wanted to stop thinking about the path.

Speaker #2: And nobody made them do that. There was no rollout. No training. No email from IT. They found something that helps. And they kept using it.

Speaker #2: Which is usually how you know what's coming. What people do on their own eventually becomes what they expect at work. And right now, there's a real gap between the two.

Speaker #3: And that's what people want out of their workday—not more tools, but fewer decisions. And none of this is new, really. Work always lags behind life.

Speaker #2: The last one there's some research that's been getting passed around about how AI pilots don't show a measurable return. And people have taken that to mean that the technology doesn't work.

Speaker #3: It did with the phones in your pockets. And it did with video calls. It did with every tool that felt normal at home for years before it felt normal at the office.

Speaker #3: So people improvise. They find a workaround. They'll use AI on their phones, on tools nobody bought them, because it makes their workday a little better.

Speaker #2: I think it's worth knowing what that study measured. It was an MIT report. It looked at whether a pilot moved the P&L within about six months.

Speaker #3: And nobody made them do that. There was no rollout, no training, no email from IT. They found something that helps, and they kept using it.

Speaker #2: And a lot of what it looked at was sales and marketing, where six months is still mid cycle. So there were essentially measuring before the thing finished happening.

Speaker #3: Which is usually how you know what's coming. What people do on their own eventually becomes what they expect at work. And right now, there's a real gap between the two.

Speaker #2: A new hire doesn't move P&L in six months either. So it's not a damning finding. It really is just a short window. Within that same study, there's a second number that almost got no attention.

Speaker #3: The last one—there's some research that's been getting passed around about how AI pilots don't show a measurable return, and people have taken that to mean that the technology doesn't work.

Speaker #2: When companies brought in a specialist to deploy, it reached production about two thirds of the time. When they built it themselves, about a third.

Speaker #2: So we're looking at twice the success rate here. And here's why it's interesting. It's not a technology gap. Everybody has access to the same models.

Speaker #3: I think it's worth knowing what that study measured. It was an MIT report. It looked at whether a pilot moved the P&L within about six months.

Speaker #2: You can buy the same capability on a credit card. The gap is entirely in the execution. A few reasons for it. And none of them are exotic.

Speaker #3: And a lot of what it looked at was sales and marketing, where six months is still mid-cycle. So they were essentially measuring before the thing finished happening.

Speaker #3: A new hire doesn't move P&L in six months, either, so it's not a damning finding. It really is just a short window. Within that same study, there's a second number that almost got no attention.

Speaker #2: The specialist has done it before. They solved the integration problem. The permissions problem. The governance problem. 100 times. The internal team is solving each one for the first time.

Speaker #2: While also doing 17 other things. The tools that work great for you individually often stall inside a company because they're flexible. But they don't learn the specific workflow you dropped them into.

Speaker #3: When companies brought in a specialist to deploy, it reached production about two-thirds of the time. When they built it themselves, about a third.

Speaker #3: So we're looking at twice the success rate here. And here's why it's interesting: it's not a technology gap. Everybody has access to the same models.

Speaker #2: And internal projects almost always underestimate the boring half. The plumbing, the data access, the edge cases. Demos run on clean examples. Real companies are nothing but edge cases.

Speaker #3: You can buy the same capability on a credit card. The gap is entirely in the execution. There are a few reasons for it, and none of them are exotic.

Speaker #2: That's how you end up in pilot purgatory for a year and a half. There's also a control thing. Building it yourself feels like control.

Speaker #3: The specialist has done it before. They solved the integration problem, the permissions problem, the governance problem—100 times. The internal team is solving each one for the first time.

Speaker #2: In practice, it usually means fewer people, slower iteration, and a pile of technical debts. But the reason I find this encouraging rather than discouraging is that none of those are technology problems.

Speaker #3: While also doing 17 other things. The tools that work great for you individually often stall inside a company because they're flexible, but they don't learn the specific workflow you dropped them into.

Speaker #2: Every single one is solvable by a team that's done it before. Nobody's waiting on a breakthrough. The capability is here. The practice is just catching up.

Speaker #3: And internal projects almost always underestimate the boring half: the plumbing, the data access, the edge cases. Demos run on clean examples. Real companies are nothing but edge cases.

Speaker #2: I'll say one honest thing though. Because I don't think it helps anyone if I only give you the tidy version of the story. Buy first isn't universal.

Speaker #2: If you got proprietary data, a general model can't touch, or genuinely unusual workflow, or you're in a regulated high risk situation, building can be the right call.

Speaker #3: That's how you end up in pilot purgatory for a year and a half. There's also a control thing: building it yourself feels like control.

Speaker #3: In practice, it usually means fewer people, slower iteration, and a pile of technical debt. But the reason I find this encouraging rather than discouraging is that none of those are technology problems.

Speaker #2: It's just not the defaults anymore. So three things. The pressure landed on information work, not physical work. Which means the businesses that were hardest to grow might be the ones this helps first.

Speaker #3: Every single one is solvable by a team that's done it before. Nobody's waiting on a breakthrough. The capability is here—the practice is just catching up.

Speaker #2: And the second, we all got personalized intelligence everywhere in our lives, except the place we spent 40 hours a week. That gap is the opportunity.

Speaker #3: I'll say one honest thing, though, because I don't think it helps anyone if I only give you the tidy version of the story. "Buy first" isn't universal.

Speaker #2: And lastly, the technology is proven. What's still being worked out is how you put it in. And that's a variable that decides whether any of this pays off.

Speaker #3: If you’ve got proprietary data a general model can’t access, or a genuinely unusual workflow, or you’re in a regulated, high-risk situation, building could be the right call.

Speaker #2: Happy to get into any of it.

Speaker #1: Yeah. And thank you, Zoe. That's great table setting for us in the context. And we're really lucky. Zoe is flying around probably the world.

Speaker #3: It's just not the defaults anymore. So, three things. The pressure landed on information work, not physical work. Which means the businesses that were hardest to grow might be the ones this helps first.

Speaker #1: But I'll say at least the States. Going to different customers. And she's really seeing what's happening out there. And so I think you mentioned that these are not just trends that you're reading about.

Speaker #1: You're actually seeing them. And I was really taken away by a lot of that. So what we're going to do now in just to make this more interactive, we're each going to ask you a question.

Speaker #3: And second, we all have personalized intelligence everywhere in our lives, except in the place we spend 40 hours a week. That gap is the opportunity.

Speaker #1: We have a bit of a conversation. So this is fireside chat part of things. And we're just going to kind of build on everything you just talked about.

Speaker #3: And lastly, the technology has proven itself; what's still being worked out is how you put it in. And that's a variable that decides whether any of this pays off.

Speaker #1: So why don't we go in the order that you started from? And Adam, you're the expert on trades. And with your business. So go ahead.

Speaker #3: Happy to get into any of it.

Speaker #2: Yeah. And thank you, Zoe. That's great table setting for us and the context. And we're really lucky—Zoe is probably flying around the world.

Speaker #3: Thank you guys for home services over there. And Zoe, thanks for the chat. And I look forward to you taking the short flight over to Australia at some point.

Speaker #2: But I'll say, at least in the States, going to different customers—she's really seeing what's happening out there. And so I think you mentioned that these are not just trends you're reading about.

Speaker #3: My question is trades and home service businesses generate an enormous amount of operational and customer data every day. Where do you see the biggest opportunity for AI to turn that data into better decisions and ultimately better business outcomes?

Speaker #2: You're actually seeing them, and I was really taken away by a lot of that. So, what we're going to do now, just to make this more interactive, is we're each going to ask you a question.

Speaker #2: We have a bit of a conversation. So this is the fireside chat part of things, and we're just going to kind of build on everything you just talked about.

Speaker #2: Yeah. That's a great question. I think the thing is the data is all there. That's the thing. Every job a trade business does throws off information.

Speaker #2: So, why don't we go in the order that you started from? And Adam, you're the expert on trades and with your business, so go ahead.

Speaker #2: What broke. What it took to fix. How to actually get customers. What venues actually work. But it's scattered. It's in the scheduling tool. In the text thread.

Speaker #1: I think you guys call it "home services" over there. And Zoe, thanks for the chat, and I look forward to you taking the short flight over to Australia at some point.

Speaker #2: In the stack of invoices. In somebody's post-it notes. A fair amount of it is just in somebody's head. So the person and also the person who has to pull all of that together and make sense of it usually is the owner.

Speaker #1: My question is: trades and home service businesses generate an enormous amount of operational and customer data every day. Where do you see the biggest opportunity for AI to turn that data into better decisions?

Speaker #2: Who might be on the roof all day. And if it happens at 9:00 at night. Or if it happens at all. It's not really analysis at that point.

Speaker #1: And ultimately, better business outcomes?

Speaker #3: Yeah, that's a great question. I think the thing is, the data is all there. That's the thing. Every job a business does throws off information.

Speaker #2: It's whoever is still awake trying to remember whether the job was done successfully. And I think that's the gap. It's that the data exists.

Speaker #3: What broke. What it took to fix. How to actually get customers. What venues actually work. But it's scattered. It's in the scheduling tool. In the text thread.

Speaker #2: But nobody in the business had the bandwidth or the training sometimes to really sit with it and find the pattern. And the patterns are also right there.

Speaker #2: Which jobs are actually making money once you count the drive time, callbacks, and things like that. Which estimates are consistently wrong. And by how much.

Speaker #3: In the stack of invoices, in somebody's post-it notes, a fair amount of it is just in somebody's head. So, the person—and also the person who has to pull all of that together and make sense of it—usually is the owner.

Speaker #2: And what kind of work you should be taking more of. And which you keep saying yes to out of habit. And I think that's the opportunity.

Speaker #3: Who might be on the roof all day, and if it happens at 9:00 at night, or if it happens at all. It's not really analysis at that point.

Speaker #2: It's maybe less fancy or exotic than it sounds. It's just showing a business what it already knows that has never been able to see in one place.

Speaker #3: It's whoever is still awake, trying to remember whether the job was done successfully. And I think that's the gap—it's that the data exists.

Speaker #2: And turning that into something they can really act on on Monday morning. And for this to be not something that just relies on the owner.

Speaker #2: But as the business grows and scale, it could become shared understanding that the team can mobilize together on.

Speaker #3: But nobody in the business had the bandwidth or the training, sometimes, to really sit with it and find the pattern. And the patterns are also right there.

Speaker #1: Yep.

Speaker #3: Which jobs are actually making money once you count the drive time, callbacks, and things like that? Which estimates are consistently wrong, and by how much?

Speaker #3: Thanks, Zoe. I appreciate that.

Speaker #1: Hey. Sorry. I jumped in. I'm excited. As a person that's been spending the last 20 years on math, indoor math, you struck a chord with me.

Speaker #3: And what kind of work you should be taking more of, and which you keep saying yes to out of habit. And I think that's the opportunity.

Speaker #1: Not just indoors. When I'm driving, nobody really cares about how to get there. I mean, remember we had the math question. You had to really figure out.

Speaker #3: It’s maybe less fancy or exotic than it sounds. It’s just showing a business what it already knows but has never been able to see in one place.

Speaker #1: I just want to arrive. You got the blue dot. And you're in the center of the universe. And it's so easy now. I mean, it's actually a point that we don't have to think.

Speaker #3: And turning that into something they can really act on Monday morning. And for this to not be something that just relies on the owner, but as the business grows and scales, it can become a shared understanding that the team can mobilize together on.

Speaker #1: And you were building on what I was talking about being the person being the integration layer. And then you started to quantify what that coordination tax that overhead of the things that we don't even think about.

Speaker #1: Yeah. It's easy. I can just look. And I can find a place to go. I can navigate things. But we've talked a lot about sort of the neuroscience behind that.

Speaker #1: Yep.

Speaker #2: Thanks, Zoe. I appreciate that.

Speaker #4: Sorry, I jumped in. I'm excited. As a person who's spent the last 20 years on math—indoor math—you struck a chord with me.

Speaker #1: And you were really getting at it like, this is actually impacting productivity. And we also know that it's like a screeching slide into sandpaper.

Speaker #4: Not just indoors. When I'm driving, nobody really cares about how to get there. I mean, remember we had the math question—you had to really figure it out.

Speaker #1: You're coming to work. You've got all these great tools, like Waze and everything that helps you navigate seamlessly. And then you get in the building.

Speaker #4: I just want to arrive. You’ve got the blue dot, and you’re in the center of the universe. And it’s so easy now. I mean, it’s actually a point that we don’t have to think.

Speaker #1: You're like, Where did it go? Right? And now I'm back to the manual stuff. So if we can get to a place where the building truly knows me as well as my phone and my personal tools, and we can get over that sort of overhead tax of people having to figure those things out, what do you think what are you seeing in the research as to what would that mean?

Speaker #4: And you were building on what I was talking about, being the person, being the integration layer. And then you started to quantify what that coordination tax is—that overhead of the things that we don't even think about.

Speaker #4: Yeah, it's easy. I can just look and I can find a place to go. I can navigate things. But we've talked a lot about sort of the neuroscience behind that.

Speaker #1: I mean, I'm sure there's business outcomes. There's probably what's the extent of it on the human experience? And maybe the business outcome?

Speaker #4: And you were really getting at it; like, this is actually impacting productivity. And we also know that it's like a screeching slide into sandpaper.

Speaker #2: Yeah. I mean, I think the top thing that's jumping out for me is decision capacity. Right? We I mean, human beings as just normal typical human being, there's a finite amount of just a good decisions that I have on a daily basis.

Speaker #4: You're coming to work. You've got all these great tools like Waze and everything that helps you navigate seamlessly. And then you get in the building.

Speaker #4: You're like, "Where did it go?" Right? And now I'm back to the manual stuff. So, if we can get to a place where the building truly knows me as well as my phone and my personal tools, and we can get over that sort of overhead tax of people having to figure those things out, what do you think? What are you seeing in the research as to what that would mean?

Speaker #2: And right now, I think a lot of that bandwidth is kind of wasted on the minute details that just had to surround the actual job itself.

Speaker #2: So being able to gain back that cognitive reserve to focus on the things that are more important that are more critical synthesizing really understanding patterns creating that is, I think, what's really out there.

Speaker #4: I mean, I'm sure there are business outcomes. There's probably—what's the extent of it on the human experience? And maybe the business outcome?

Speaker #2: I would add another really important aspect that's just starting to surface. It's also the mental space for people to focus on what makes us human, which is building connections and relationships with other people.

Speaker #3: Yeah. I mean, I think the top thing that's jumping out for me is decision capacity. Right? We I mean, human beings as just normal typical human being, there's a finite amount of just a good decisions that I have on a daily basis.

Speaker #2: I think hybrid work and digital-first ways of working has been fantastic. And with all of the technologies making sure that people can still get the work done, no matter where they are.

Speaker #3: And right now, I think a lot of that bandwidth is kind of wasted on the minute details that just have to surround the actual job itself.

Speaker #2: But when people are in person with each other in a physical building, you really want people to have the not only the time, but also the mental capacity to do is have a real conversation with somebody.

Speaker #3: So being able to gain back that cognitive reserve to focus on the things that are more important, that are more critical—synthesizing, really understanding patterns, creating—that is, I think, what's really out there.

Speaker #2: And actually start to build that connection. Build a community. Build an environment that's helping each other to learn. So I think those are all really critical moments.

Speaker #3: I would add another really important aspect that's just starting to surface: it's also the mental space for people to focus on what makes us human, which is building connections and relationships with other people.

Speaker #2: That I in an ideal world, where AI frees us from the minute details that I have to decide, then I can just really focus on experiencing the presence and all of the connections.

Speaker #3: I think hybrid work and digital-first ways of working have been fantastic. And with all of the technologies, we’re making sure that people can still get work done, no matter where they are.

Speaker #1: Yeah. You just made me think about something actually. When you sort of adding this all up as a thought experiment, would it what if you said earlier, maybe it's 10 minutes a day.

Speaker #3: But when people are in person with each other in a physical building, what you really want people to have—not only the time, but also the mental capacity to do—is have a real conversation with somebody.

Speaker #1: Maybe it's 20 minutes. I don't know what the exact numbers for the coordination tax. But what if I traded those minutes exactly for high value moments?

Speaker #1: Like some of the customers call them moments that matter. Right? So if I wasn't spending 10 minutes doing all this mundane friction tasks of booking meetings or whatever, and I had a meaningful conversation with you.

Speaker #3: And actually start to build that connection. Build a community. Build an environment that's helping each other to learn. So I think those are all really critical moments that I—in an ideal world—where AI frees us from the minute details that I have to decide.

Speaker #1: And maybe we found out that we love the same food or something like maybe we found out that talked about something about a project.

Speaker #3: Then I can just really focus on experiencing the presence and all of the connections.

Speaker #1: So I think that's an interesting idea just to go if I could trade minute for minute for something that's high value, strategic, culture, connection, it's very subjective.

Speaker #4: Yeah, you just made me think about something, actually. When you sort of add this all up as a thought experiment—what you said earlier—maybe it's 10 minutes a day.

Speaker #1: I get that. But there could be some pretty interesting outcomes. So all right. Well, we'll parking lot that one. And Kerem, I'll turn it over to you.

Speaker #4: Maybe it's 20 minutes. I don't know what the exact numbers are for the coordination tax. But what if I traded those minutes exactly for high-value moments?

Speaker #4: Yeah. It's fascinating conversation. Thank you, Zoe, for joining us. So I think your last trend was on the deployment. And I don't want to throw a curveball.

Speaker #4: Some of the customers call them moments that matter, right? So if I wasn't spending 10 minutes doing all these mundane, friction tasks of booking meetings or whatever, and I had a meaningful conversation with you.

Speaker #4: But I want to put the context in terms of the next generation. Younger my kids or others who are just coming into the workforce who have been coding for half their life.

Speaker #4: And maybe we found out that we love the same food or something. Maybe we found out that we talked about something related to a project. So I think that's an interesting idea—just to go, if I could trade minutes for minutes for something that's high value, strategic, culture, connection. It's very subjective.

Speaker #4: They're 18. But they've been coding for more than half their life. So they also already experts of AI. They already know how to code it.

Speaker #4: So when you think about deployment, every one of them is their own vibe coder, is their own developer, thinks they're the best than anybody else.

Speaker #4: I get that. But there could be some pretty interesting outcomes. So, all right, we'll park and lot that one. And Khurram, I'll turn it over to you.

Speaker #4: So how do you see this evolving in terms of with we see new models coming every day. We see new tools coming every day.

Speaker #4: Everything changes so fast. Right? How do you see this to be a scalable motion from a deployment? How does it get scale? Not with millions of different things, but a motion that you feel like it's going to get deployed at scale for the enterprise?

Speaker #5: Yeah, it's a fascinating conversation. Thank you, Zoe, for joining us. So I think your last trend was on the deployment, and I don't want to throw a curveball.

Speaker #5: But I want to put the context in terms of the next generation—young people, my kids, or others who are just coming into the workforce, who have been coding for half their life.

Speaker #2: Yeah. I'll answer that part based on what I can see from inside companies, which is more on the adoption side rather than the distribution side.

Speaker #5: They're 18, but they've been coding for more than half their life, so they're also already experts in AI. They already know how to code it.

Speaker #2: And I think and here's where mid-market is becoming really interesting. Right? Because it's the second that it's the segment that moves the fastest. They may not be the most resourced, but they are the fastest they might not have an AI center of excellence.

Speaker #5: So when you think about deployment, every one of them is their own vibe coder, their own developer—thinks they're the best, better than anybody else.

Speaker #5: So, how do you see this evolving, in terms of—we see new models coming every day. We see new tools coming every day.

Speaker #2: They don't have a two-year roadmap. Right? But that turns out to be an advantage because there are fewer people that you need to agree to make a move on something.

Speaker #5: Everything changes so fast, right? How do you see this being a scalable motion from a deployment perspective? How does it scale—not with millions of different things, but a motion that you feel is going to be deployed at scale for the enterprise?

Speaker #2: So what they don't have is someone whose job is to make this work. Right? In a big enterprise, you all have that experience. In a big enterprise, there's a team.

Speaker #3: Yeah, I'll answer that part based on what I can see from inside companies, which is more on the adoption side rather than the distribution side.

Speaker #2: In a 200-person company, it's somebody's fourth priority. Right? So the thing that has to be true for mass deployment is that it cannot require an owner, or a champion project plan, all of the complicated stuff.

Speaker #3: And I think and here's where mid-market is becoming really interesting. Right? Because it's the second that it's the segment that moves the fastest. They may not be the most resourced.

Speaker #2: It doesn't scale into that segment. And what it has to do is it has to spread the way things actually spread in the smaller company.

Speaker #3: But they are the fastest. They might not have an AI center of excellence. They don't have a two-year roadmap, right? But that turns out to be an advantage because there are fewer people that you need to agree with to make a move on something.

Speaker #2: I love the example that you mentioned with a younger generation that are essentially AI natives. Right? How do they know which app is the trendiest to want to use?

Speaker #2: How do they know which video editing app is the best? Somebody uses it. And it's visible. Right? If visible saves them time, where if visibly deliver better results and the person next will go ask them, oh, what is that thing that you used?

Speaker #3: So, what they don't have is someone whose job is to make this work. Right? In a big enterprise—you all have that experience—in a big enterprise, there's a...

Speaker #1: In a 200 person company . It's somebody's first priority , right ? So the thing that has to be true for mass deployment is that it cannot require an owner or like a champion , a project plan .

Speaker #2: Right? That's the whole mechanism. Not necessarily orchestrated rollout or training session, but just one person's day getting noticeably better in front of other people.

Speaker #1: All of the complicated stuff—it doesn't scale into that segment. And what it has to do is, it has to spread the way things actually spread in the smaller company.

Speaker #2: I think that's that would be I think from a behavioral perspective, what would really help with adoption.

Speaker #4: No, that's interesting. And I agree with you. I think it's that we see that in our enterprise business, where we get referrals. But I think this is a more viral set of referrals that happened just because somebody uses it and finds it amazing.

Speaker #1: I love the example that you mentioned with the younger generation that are essentially AI natives , right ? How do they know which app is the is the trendiest one to use ?

Speaker #1: How do they know which video editing app is the best? Somebody uses it and it's visible, right? If it's visible, it saves them time or visibly delivers better results.

Speaker #4: And then the next person sees the same thing. So cool.

Speaker #1: And I think Kerem on that note also this is where I've talked about value-based selling. The whole market has shifted. We are in 30-day or less commitments in a lot of cases on the products that are coming out.

Speaker #1: And the person next will go ask them , oh , what is that thing that you used ? Right ? That's the whole mechanism , not necessarily orchestrated rollout or training session , but just one person's day getting noticeably better in front of other people .

Speaker #1: People have to see value. In mid-market, I think the threshold is that much higher. It's like, yeah, this is working for me. Nobody's forcing me to use this.

Speaker #1: I'm going to use it. I'm going to love it. I'm going to tell people. And I think the onus is on companies like us, the ones that are deploying it.

Speaker #1: I think that would be, I think, from a behavioral perspective, what would really help with adoption.

Speaker #1: We have to make it first easy to deploy. There's no patience for these giant integrations at smaller companies. And people have to love it.

Speaker #2: No , that's interesting . And I agree with you . I think it's that we see that in our enterprise business where we get referrals .

Speaker #1: I mean, that's the whole thing. And it has to stay fresh and being used all the time. So yeah. Anyways, there's so much more we could talk about.

Speaker #2: But I think this is a more viral set of referrals that happen just because somebody uses it and finds it amazing, and then the next person sees the same thing.

Speaker #4: I'm going to close off with Adam because when I first met Adam, he and I have a joint background of working at a large telco, like you were a teletraveler's friend.

Speaker #2: So cool .

Speaker #3: I think , I think on that note , also , you know , this is where I was talking about value based selling .

Speaker #3: The whole market has shifted . We are in , you know , 30 day or less commitments in a lot of cases on the products that are coming out .

Speaker #4: And then progressing through our careers, we've gone to the mid-market. And so maybe Adam, you want to close off to say, what is your experience with the mid-market?

Speaker #3: People have to see value in mid-market . I think the threshold is that much higher . It's like , yeah , this is working for me .

Speaker #4: And how do you see this evolving?

Speaker #3: I look like I love the mid-market. Because they make decisions rapidly. And they're very much focused on outcome. So as long as everything you do is related back to an outcome, not a metric, it's an actual business outcome, then they don't have to sit there and go, well, it's not in this year's budget or whatever.

Speaker #3: Nobody's forcing me to use this . I'm going to use it . I'm going to love it . I'm going to tell people , and I think the onus is on companies like us , the ones that are employing , deploying it .

Speaker #3: We have to make it, first, easy to deploy. There's no patience for these giant integrations at smaller companies, and people have to love it.

Speaker #3: I mean , that's the whole thing . And it has to stay fresh and being used all the time . So yeah , anyways , there's so much more we could talk about .

Speaker #3: It's like, well, that makes sense if I spend $2, I make $10. Go. Right?

Speaker #2: I'm going to close off with Adam because when I first met Adam, he and I had a joint background of working at a large telco, like you were at Telstra.

Speaker #4: Yeah.

Speaker #3: So I could have happily built something for enterprise, but I was like, no, mid-market is where the acceleration is. Mid-market is where the adoption is.

Speaker #2: I was a sprint and then progressing through our careers . We've gone to the mid . And so maybe Adam , you want to close off to say what is your experience with mid-market and how do you see this evolving

Speaker #3: Mid-market is where the speed is. But you are right, Zoe, in that part of it is recognizing that they don't have that support layer internally, like for us, wherever dealing with the owner or one level down perhaps.

Speaker #4: I look , I , I love the mid-market because they , they make decisions rapidly and they're very much focused on outcome . So as long as , as long as everything you do is related back to an outcome , not , not a metric .

Speaker #3: Right? Who indirectly deals with the owner. Right? Or directly deals with the owner. So that's why the model that we do mid-market, you have to basically be that capacity.

Speaker #4: It's an actual business outcome . Then , you know , they don't have to sit there and go , well , it's not in this year's budgets or whatever .

Speaker #4: It's like , well , that makes sense . If I spend $2 , I make $10 , go , right . So , you know , I could have happily built something for enterprise , but I was like , no , mid-market is where the acceleration is .

Speaker #3: Right? To enable them to do it. And you just have to accept that. And that's built into the model.

Speaker #1: All right. Well, thank you so much, Zoe. Zoe, we could talk for hours. I'm sure we will. Great conversation. Great insights. And I'm sure we'll have you back as a guest again.

Speaker #4: Mid-Market is where the adoption is . Mid-Market , where the speed is . So , but you are right , Zoe , in that part of it is recognizing that they don't have that support layer , internal internally , like , like for us , we're either dealing with the owner or one level down , perhaps , right ?

Speaker #1: And thank you very much. I think we're going to now. Move to Kerem has some closing words. And we have some more Q&A. So Adam and I will stick around.

Speaker #4: Yep. So I've got a couple of questions that came in. So I'm going to get you guys help on that. So one question came in.

Speaker #4: indirectly deals with the owner , right ? So or directly deals with the owner . So that's why the model that we do mid-market , you have to basically be that capacity , right ?

Speaker #4: And I'll start with it. And then, Chris, you can double down. Has the Google partnership helped at all? And how? It's a very good question.

Speaker #4: And we've been using Google on both sides, helping us with the cloud infrastructure and helping with getting all our clients are on most of them are on Google Cloud, which is great.

Speaker #4: To enable them to do it. And you just have to accept that. And that's built into the model.

Speaker #3: All right . Well thank you so much . Joy . Zoe , we could talk for hours . I'm sure we will . Great conversation .

Speaker #4: And getting them the advanced products and access. And then we've also, as Chris mentioned, working on the Google Marketplace to launch the mid-market, which we think is a huge opportunity.

Speaker #3: Great insights . And I'm sure we'll have you back as a guest again . And thank you very much . I think we're going to now move to , you know , quorum has some closing words and we have some more Q&A .

Speaker #4: So we work regularly with the Google team. But I'll tell you one thing that happened, I think Chris was showing you the events module.

Speaker #3: So, Adam and I will stick around.

Speaker #2: Yep. So I've got a couple of questions that came in, so I'm going to get you guys' help on that. One question came in, and I'll start with it.

Speaker #4: And I'm proud to say Orange Ring team working with the Google team, got that product done, literally in Chris has the exact numbers. But I think it's within a quarter or less.

Speaker #2: And then Chris , you can double down Has the Google partnership helped at all . And how . It's a very good question .

Speaker #4: So it is an amazing ground zero to now production. So maybe, Chris, you want to expand how Google helped you there.

Speaker #2: And you know , we've been using Google on both sides helping us with you know the cloud infrastructure and helping with , you know , getting all our clients are on most of them are on Google Cloud , which is great .

Speaker #1: Yeah. So I also want to make something clear. That it didn't go so fast because it's easy. It went so fast, A, we've got a lot of IP around this.

Speaker #1: I mentioned in my presentation. There were the last number of years, is highly sophisticated, highly proprietary. And what is why we win these complex deals.

Speaker #2: And getting them the advanced products and access. And then we've also, as Chris mentioned, been working on the Google Marketplace to launch the mid-market, which we think is a huge opportunity.

Speaker #2: So we work regularly with with Google team . But I'll tell you one thing that happened . I think Chris was showing you the events module , and I'm proud to say our engineering team , working with the Google team , got that product done literally in .

Speaker #1: So we understand. Things are managed in the workspace. So we had all of these parts and pieces don't forget, we also have integrations with these customers that already into their core systems, their ticketing systems, their directory systems.

Speaker #2: Chris has the exact numbers , but I think it's within a quarter or less . So it is an amazing ground zero to now , you know , production .

Speaker #1: And so the Google team working with the our partners and our internal team, we glued it all together. And created what is a seamless, orchestrated workflow.

Speaker #2: So maybe, Chris, you want to expand on how Google helped you there.

Speaker #3: So yeah, so I also want to make something clear: that it didn't go so fast because it's easy. It went so fast.

Speaker #1: And so it's really, yes, it went fast. And it's new. But it's really a combination of our features and modules that's very specific to how our customers do business.

Speaker #3: A, we've got a lot of IP I mentioned in my presentation. Over the last number of years, it is highly sophisticated, highly proprietary.

Speaker #1: Now, where does Google come in next? Well, it's a hyperscaler. Right? We first of all, we're working in secure environments. We have ultra-high security.

Speaker #3: And that is why we win these complex deals. We understand how things are managed in the workspace. So we had all of these parts and pieces.

Speaker #1: On our own platforms and for our customers. And next, we're going to be in the marketplace. So when people part of the whole buying cycle is going through contracting and going through all those motions and then delivering, well, that's all now going to be through the marketplace so that somebody can just sign up, buy it, do a click-through ULA, pay for it, get the product.

Speaker #3: Don't forget, we also have integrations with these customers that are already into their core systems or ticketing systems, their directory systems. And so, the Google team, working with our partners and our internal team, we glued it all together and created what is a seamless, orchestrated workflow.

Speaker #1: There might be a couple of integrations afterwards. But the time to value is super important. And for all those reasons, this is really where we go from small quantity to prime-time scale.

Speaker #3: And so it's really yes , it's , it went fast and it's new , but it's really a combination of our features and modules .

Speaker #3: It's very specific to , to how our customers do business . Now , where does Google come in next ? Well , it's a hyperscaler , right ?

Speaker #4: Yeah. That's great. That's great. OK, next question I have is, what are the major synergies between legacy builds and what do you expect to go for OPEX levels to be quarterly?

Speaker #3: We first of all , we're working in secure environments . We have , you know , ultra high security on our own platforms and for our customers .

Speaker #3: And next we're going to be in the marketplace . So when people part of the whole buying cycle is going through contracting and going through all those motions , and then delivering , well , that's all now going to be through the marketplace so that somebody can just sign up , buy it , do a click through , you'll pay for it , get the product .

Speaker #4: So I'll start then. And I'll hand it off to Adam to give his input as well. But I can tell you right now and Adam can tell his philosophy of how we runs his OPEX models.

Speaker #4: Right? But I would tell you right now is that there's a huge opportunity for synergy. As we combine the businesses, we have the common infrastructure, the cloud infrastructure we talked about.

Speaker #3: You know , there might be a couple integrations afterwards , but the time to value is super important . And , you know , for all those reasons , like this is really where we go from , you know , small quantity to prime time scale

Speaker #4: Adam also, by the way, uses Google ecosystem extensively. Not only for the services, but also for Google Ads and other things he does with his clients.

Speaker #2: Yeah . That's great . That's great . Okay . Next question I have is what are the what are the major synergies between legacy builds and what do you expect the go forward opex levels to be quarterly ?

Speaker #4: So there's an expanded relationship there. So there's a synergy factor there in terms of our relationship. But all in all, when you think about our business, we're going to leverage Adam's distribution channel.

Speaker #4: He's going to leverage our enterprise access and channel. So there's going to be lots of synergies there. On core infrastructure and locations, he's based in Manila.

Speaker #2: So I'll start there and I'll hand it off to Adam to to give his input as well . But I can tell you right now , Adam can tell his philosophy of how he how he his OpEx models , right .

Speaker #4: We're in Manila as well. There's synergies there. As we think about growing the teams, it's one team under the sky umbrella. And leveraging all the shared infrastructure costs, we think there's significant opportunity there.

Speaker #2: But what I would tell you right now is that there's a huge opportunity for synergy. You know, as we combine the businesses, we have the common infrastructure, the cloud infrastructure.

Speaker #2: We talked about , you know , Adam , also , by the way , uses Google ecosystem extensively , not only for , you know , the services , but also for Google ads and other things he does with his clients .

Speaker #4: So those realizations as I mentioned in my chart are going to happen over the next 6 to 12 months. Some actually are happening this quarter, as you can see some of the impact.

Speaker #4: But they're going to start happening very quickly in Q3 and Q4 and early next year as well. So I'm excited about that. But maybe, Adam, you want to talk about your OPEX strategy, how you're managing your OPEX?

Speaker #2: So there's a , there's an expanded relationship there . So there's a synergy factor there in terms of relationship . But all in all , when we think about our business , we're going to leverage Adam's distribution channel .

Speaker #2: He's going to leverage our enterprise access and channel, so there are going to be lots of synergies there on core infrastructure and locations.

Speaker #3: Yeah. And I is that business models always been about profitability, sustainability. Moving forward, we last took capital on board, I think, seven, eight years ago from memory.

Speaker #2: You know , he's based in Manila . We're in Manila as well . There's synergies there as we think about , you know , growing the teams .

Speaker #2: It's one team under the Sky umbrella and leveraging all the shared infrastructure costs . We think there's significant opportunity there . So those realizations , as I mentioned in my chart , are going to happen over the next 6 to 12 months .

Speaker #3: So we have always focused on, from an OPEX point of view, that we would be significantly below the revenue side. So we can invest in a sustainable way.

Speaker #2: Some actually are happening this quarter . As you can see , some of the impact , but they're going to start happening very quickly in Q3 and Q4 .

Speaker #3: So look, I think the key is what Kerem touched on before. And this is the pathway that we're going through at the moment. What's the operational costs that can be reduced as a percentage that we cross over?

Speaker #2: And then early next year as well . So , so I'm excited about that . But maybe , Adam , you want to talk about your opex strategy , how you how you're managing your , your OpEx

Speaker #3: And I think that's really the process that we're going through at the moment. Because there's a lot of aspects of that. But I'm sure we'll be reporting on those in the future as we succeed in that area.

Speaker #4: Yeah. And I think the important thing is that our business model has always been about profitability and sustainability moving forward. We last took capital on board.

Speaker #4: OK, last question. I'll give it to Chris. So Chris, the question is, you announced a lot of great new products. You've got the Flow and Beat and events and stuff.

Speaker #4: I think , 7 or 8 years ago from from memory . So , you know , we we have always focused on from an opex point of view that we would be significantly below the revenue side .

Speaker #4: So we can invest in a sustainable way . So look , I think I think the key is what Karen touched on before , and this is the pathway that we're going through at the moment .

Speaker #4: What is your competitive moat for a small company like CXAI? How are you creating that competitive moat? Because a lot of people vying for those kind of products.

Speaker #4: What's the operational cost that can be reduced as a percentage that we cross over? And I think that's really the process that we're going through at the moment.

Speaker #4: So what is the sky moat?

Speaker #1: Yeah. Well, we've got a number of different things here. And I touched on it earlier. And one of them is just IP. I'll start with and I'm not relying on this.

Speaker #4: You know , because there's a lot , a lot , a lot of a lot of aspects of that . But I'm sure we'll be reporting in those in the future as , as we succeed in that area

Speaker #1: But we've got enterprise customers. We've proven technology. We have been deployed in some of the world's toughest, most complex environments at scale. This is not just a demo happening.

Speaker #2: Okay . Last question I'll give to Chris . So Chris , question is , you announced a lot of great new products . You've got the flow and and beat and events and stuff .

Speaker #1: We're talking about thousands and thousands of users at these organizations. And reliably delivering that. Beyond that, when I really think about today's market, it's all about our ability to differentiate.

Speaker #2: What is your competitive moat ? You know , for a small company like , like Cxci , how are you creating that competitive mode ?

Speaker #1: And how do we do that? Well, one of them is just on the even on the cost side. When we talked about our agentic AI, Bond and Cortex is truly different in the market.

Speaker #2: Because a lot of people , you know , vying for those kind of products . So what is the , what is , what is the sky mode ?

Speaker #1: We are able to do LLM at a fraction of the cost. So something that somebody is doing in one of the main LLMs is costing a cent and not tens of dollars.

Speaker #3: Yeah , we've got a number of different things here . And I touched on it earlier . And one of them is just IP .

Speaker #1: So that's a huge moat. We've got the IP around contact and spatial awareness. OK? So this is something that other companies do not have.

Speaker #3: I'll start with , and I'm not relying on this , but we've got enterprise customers . We've proven technology . We have been deployed in some of the world's toughest , most complex environments at scale .

Speaker #1: We understand what's going on in space. We've got all these integrations, which is giving us connectivity and it's increasing the enhancing the user experience.

Speaker #3: This is not just a demo happening. We're talking about thousands and thousands of users at these organizations, and reliably delivering that.

Speaker #1: It's also creating all that data. So when you saw me demoing about asking these questions by conversation and getting highly analytical or insightful answers, that's coming through all of those integrations.

Speaker #3: You know , beyond that , when I really think about today's market , it's all about our ability to differentiate and how do we do that ?

Speaker #3: Well , one of them is just on the even on the cost side , when we talk about our authentic AI bond and cortex is truly different in the market , we are able to do LM at a fraction of the cost .

Speaker #1: And so we're really at the center of this. I mean, the company grew up bringing together events, maps, workplace, and when this became CXAI, it was based on delivering agentic AI.

Speaker #3: So something that somebody is doing in one of the main LMS is costing us cents and not, you know, tens of dollars.

Speaker #3: So that's a huge moat. We've got the IP around contact context and spatial awareness. Okay, so this is something that other companies do not have.

Speaker #1: So I think we're leaps and bounds ahead of understanding how to deliver agentic AI. And you said it right at the beginning of the presentation.

Speaker #1: This is not another chatbot or an assistant. This is an agentic solution that does things for you. And that's what people want. We don't want the overhead of having to answer everything manually or set up a meeting manually.

Speaker #3: We understand what's going on in space . We we've got all these integrations , which is giving us connectivity . And it's increasing , enhancing the user experience .

Speaker #3: It's also creating all that data . So when you saw me demoing about asking these , questions by conversation and getting highly , you know , analytical or insightful answers , that's coming through all of those integrations .

Speaker #1: It's going to do it for us. So at the end of the day, if you ask me, I think it's user experience. And we talked about it all through this.

Speaker #1: People are loving the product. And they tell people about it. And it becomes viral within those organizations. And of course, all the referrals that we get.

Speaker #3: And so we're , we're really at the center of this . I mean , the company grew up bringing together events , maps , workplace , and when this became Cxci , it was based on delivering agentic AI .

Speaker #1: Because people are super happy with the products.

Speaker #4: Yeah. Great. Well, thank you, gents. Really appreciate it. We're going to head to my last slide or last two slides. And I know we're at the top of the hour, but we'll go a few more minutes here.

Speaker #3: So I think we're leaps and bounds ahead in understanding how to deliver agentic AI. And you said it right at the beginning of the presentation.

Speaker #4: Thanks, Chris. Thanks, Adam. All right. So let me leave you all with this. I spent my career around major technology transitions. And I believe agentic AI will be one of the most consequential.

Speaker #3: This is not another chatbot or an assistant. This isn't an agentic solution that does things for you. And that's what people want.

Speaker #3: We don't want the overhead of having to, you know, answer everything manually or set up a meeting manually. It's going to do it for us.

Speaker #4: And I don't mean that lightly. And I don't believe the winners will simply be the companies with the biggest models. I believe enormous value will be created by companies that understand context.

Speaker #3: So, at the end of the day, if you ask me, I think it's user experience, and we talked about it all through this.

Speaker #3: People are loving the product, and they tell people about it, and it becomes viral within those organizations. And, of course, all the referrals that we get are because people are super happy with the products.

Speaker #4: And turn that context into action. That is the company we are building. That is what CXAI is about. We started with the workplace. Now we're expanding from place to person to business.

Speaker #2: Yeah , great . Well , thank you gents . Really appreciate it . We're going to head to my last slide or last two slides .

Speaker #2: And I know we're at the top of the hour , but we'll go a few more minutes here . Thanks , Chris . Thanks , Adam .

Speaker #4: These are the three forms of context. Place through our Flow product. Which tells you where and how people work. Person through Beat. What an individual and team need to accomplish.

Speaker #2: All right. So let me leave you all with this. I have spent my career around major technology transitions, and I believe agentic AI will be one of the most consequential.

Speaker #4: And what should happen next. And business. How companies acquire customers, convert demand, and grow. That business context is significantly strengthened by engine room, as we talked today.

Speaker #2: And I don't mean that lightly. And I don't believe the winners will simply be the companies with the biggest models. I believe enormous value will be created by companies that understand context and turn that context into action.

Speaker #4: We are building the agentic operating layer for how companies work and grow. Full stop. And we're focused on it. We're really excited about it.

Speaker #2: That is the company we are building. That is what CXCI is about. We started with the workplace, and now we're expanding—from place, to person, to business.

Speaker #4: As you can see, and I want to leave you with three things. I said at the start of the call, and I thank you for your patience to be with us for nearly two hours here.

Speaker #2: These are the three forms of context: place, through our flow product, which tells you where and how people work; person, through Beat, what an individual and team need to accomplish and what should happen next.

Speaker #4: But if you remember only three things from today's call, I want them to be these. Number one, we have changed the scale of CXAI, sky.

Speaker #4: We have moved from roughly a 4 million annualized revenue company at the beginning of this year to a combined platform with more than 12 million of annualized revenue scale.

Speaker #2: And business how companies acquire customers , convert , demand and grow that business context is significantly strengthened by engine room . As we talk today , we are building the Agentic operating layer for how companies work and grow full stop .

Speaker #4: And now we serve both enterprise and mid-market customers. Number two, sky2.io is moving from vision to commercial execution. The platform is in production. We have customer deployment starting.

Speaker #2: And we're focused on it. We're really excited about it, as you can see. And I want to leave you with three things.

Speaker #4: We have major renewals. We have new multi-year enterprise wins. And now we have engine rooms, customer base, as an additional channel through which to prove and distribute our new AI products.

Speaker #2: You know, I said at the start of the call—and I thank you for your patience to be with us for nearly two hours here.

Speaker #2: But if you remember , only three things from this , today's call , I want them to be these . Number one , we have changed the scale of Cxci sky .

Speaker #4: Three, we have a clear operating priority. Profitable growth. The next phase is not simply about adding revenue. It is about combined double-digit growth with increasing recurring revenue stronger software mix operating leverage and disciplined execution.

Speaker #2: We have moved from roughly a $4 million annualized revenue company at the beginning of this year to a combined platform with more than $12 million of annualized revenue scale.

Speaker #2: And now we serve both enterprise and mid-market customers. Number two, Sky 2.0 is moving from vision to commercial execution. The platform is in production.

Speaker #4: Our directional objective is to move toward breakeven in the second half of 2027 and profitable growth beyond that point. So I would categorize Q2 this way.

Speaker #2: We have customer deployments starting . We have major renewals . We have new multi-year enterprise wins . And now we have engine rooms , customer base as an additional channel through which to prove and distribute our new AI products .

Speaker #4: Q2 is a quarter. Q2 2026 is a quarter in which sky began moving from a workplace software company with an agentic AI vision into a scaled agentic AI platform with enterprise proof, mid-market distribution, and a credible path to profitable growth.

Speaker #2: Three we have a clear operating priority , profitable growth . The next phase is not simply about adding revenue , it is about combining double digit growth with increasing recurring revenue , stronger software mix , operating leverage , and disciplined execution .

Speaker #4: The acquisition created scale, sky2.io creates the opportunity for operating leverage. And execution from here determines the value we create. Thank you to our customers, our employees, our partners, and shareholders for your continued support.

Speaker #2: Our directional objective is to move towards breakeven in the second half of 2027, and profitable growth beyond that point. So I would categorize Q2 this way.

Speaker #4: We look forward to updating you on our progress next quarter. We plan to do that in November. And then we are also looking at another investor session in the end of the year or start of the year of 2027.

Speaker #2: Q2 is a quarter. Q2 2026 is a quarter in which Sky began moving from a workplace software company with an AI vision into a scaled agentic AI platform with enterprise proof, mid-market distribution, and a credible path to profitable.

Speaker #2: The acquisition created scale. Sky 2.0 creates the opportunity for operating leverage, and execution from here determines the value we create. Thank you to our customers.

Speaker #2: Our employees, our partners, and shareholders, thank you for your continued support. We look forward to updating you on our progress next quarter.

Speaker #2: We plan to do that in November , and then we are also looking at another investor session in the end of the year or start of the year of 2027 , but we're excited about Sky and to the Sky and beyond .