Q4 2024 Innodata Inc Earnings Call
Yeah.
Speaker Change: Good afternoon, ladies and gentlemen, and welcome to the IMO data at your implied fourth quarter and fiscal year 2024 results conference call.
At this time all lines are in listen only mode.
Speaker Change: Following the presentation, we will conduct a question and answer session. If at any time. During this call you require immediate assistance. Please press star zero for the operator.
Amy Eaglet: This call is being recorded on Thursday February 22025, I would now like to turn the conference over to Amy Eaglet <unk> General Counsel.
Speaker Change: Please go ahead.
Amy Eaglet: Thank you <unk> good.
Speaker Change: Good afternoon, everyone. Thank you for joining us today, our speakers today are Jack Apple have C. E O P and they'll tell you that I'm a racist spinelli interim CFO also on the call today is our niche pins, our Hart Senior Vice President Finance and corporate development, we'll hear from Jack first who will provide perspective.
Speaker Change: The business and then there is will follow with a review a review of our results for the fourth quarter and fiscal year 2024, well then take questions from analysts before I get started I think streamlines everyone that during this call we will be making forward looking statements, which are predictions projections.
Speaker Change: Or other statements about future events. These statements are based on current expectations assumptions and estimates and are subject to risks and uncertainties.
Speaker Change: Results could differ materially from those contemplated by these forward looking statements factors that could cause seems to be sold to differ materially are set forth in todays earnings press release, and the risk factors section of our Form 10-K forms 10-Q, and other reports and filings with the Securities and Exchange Commission.
Speaker Change: We undertake no obligation to update forward looking information. In addition, during this call we may discuss certain non-GAAP financial measures in our SEC filings, which are posted on our website you will find additional disclosures regarding these non-GAAP financial measures, including reconciliation.
Speaker Change: <unk> of those measures with comparable GAAP measures. Thank you I will now turn the call over to Jack.
Jack: Thank you Amy.
Jack: Hello, everyone.
Jack: Our Q4, 'twenty four revenue totaled $59 2 million a year over year increase of 127% for the quarter. This exceeded our projected Q4 revenue guidance of 52 million to 55 million for Q4 of 24.
Jack: Our adjusted EBITDA for the quarter was $14 1 million or 23.9% of revenue was 231% year over year increase.
Jack: For the full year 2024, we delivered $170 5 million of revenue up 96% over 2020 three.
Jack: Our full year, adjusted EBITDA was $34 6 million or 23% of revenue of 250% year over year increase.
Jack: We finished the year with $46 9 million of cash up from $13 $8 million of cash at the end of 2020 shrink.
Jack: Our $30 million credit facility remains undrawn.
Jack: We are very pleased with these results.
Jack: In the fourth quarter, we experienced accelerating business momentum across key strategic imperatives that we believe will serve our medium and long term growth plans.
Jack: I mentioned, we're achieving gives us confidence to forecast 2025 as another year of strong growth.
Jack: In terms of guidance in 2025, we will be taking the same approach we took in 2024.
Jack: We'll start the year with an initial growth forecast based primarily on one end near in Forecastable business.
Jack: And then succeeding quarters, if we win new business, we'll update the guidance.
Jack: Last year at this time, we forecasted 20% growth for 2024, then we revised this initial guidance upward multiple times through the course of the year.
Jack: One more business ultimately delivering 96% revenue growth.
Jack: We are now forecasting 40% or more revenue growth for 2025, and we will update this initial guidance through the course of the year.
Jack: Our strong business momentum as reflected in revenue growth margin expansion broadening customer relationships and continued progress on our strategic roadmap.
Jack: We are laser focused on providing big tech companies with the data engineering they require to develop generative AI frontier models.
Jack: We believe our efforts are paying off.
Jack: In Q4 in January we were awarded additional programs and expansions with our largest customer valued at approximately $24 million of annualized run rate revenue.
Jack: These newest awards expand our total annualized run rate revenue with this customer to approximately $135 million.
Jack: One is our other big Tech customers. We're also seeing accelerated demand for our services sequentially from Q3 of 2020 for Q4 2024, our revenues from our largest big tech customer grew by 8%.
Jack: Our aggregate revenues from our other seven big Tech customers grew by 115, 9%.
Jack: This increased growth by our other big Tech customers, which we hope will continue in 2020 five.
Jack: Europe's as validation of our land and expand strategy.
Jack: And we expect it will continue to diversify our revenue base.
Jack: Our confidence that you're serving other big check customers will collectively become a significant part of our revenue make up in 2025.
Jack: Is bolstered by the progress we made in Q4 and building relationships expanding work.
Jack: Securing new wings, gaining traction and earning trust.
Jack: The number of projects and pilots we have underway with these customers significantly increased in Q4.
This includes several pilots running now which hold the promise potentially of seven or even eight figure wins.
Jack: As we discussed last quarter, our strategy encompasses both services and platforms.
Jack: The services side, we intend to be a go to partner for Big Tech that are building generative AI frontier models and enterprises that seek to transform their products and operations with generative AI technologies.
Jack: We believe these are lucrative markets.
Jack: We are well suited to search.
Jack: The first focus area is big check and we believe we are positioned to benefit from big Tex aggressive planned investments agenda today are.
Following recent earnings reports from the magnificent seven it is estimated that Amazon meta Microsoft.
Jack: And Google Petrodelta bit, we'll spend a cumulative 325 billion in Capex and investments in 2025, driven by continued commitment to building out their artificial intelligent intelligence offerings.
Jack: Amazon expects capex to be over $100 billion.
Jack: Up from 83 billion in 2024 with its CEO reiterating his previous views that AI is a once in a lifetime type of business opportunity.
Speaker Change: Meta expects its 2025 capex to be between 60, and 65 billion, which even at the bottom end of this guidance is over 50% higher than its 2020 for capex of $39 2 billion.
Speaker Change: Its CEO his term 2025 as my quote defining year for AI.
Speaker Change: Microsoft Meanwhile, expects to spend 80 billion in its fiscal 2025, which will end in June and alphabet. His forecast 2025, Capex of 75 billion, which is almost 50% higher than in 2020 for Capex was $52 5 billion.
Speaker Change: These recent earnings press releases have reinforced the commitment by these large tech companies to accelerate their our AI investments with the goal of approaching a Gi artificial general intelligence.
Speaker Change: We believe that the long road to Agi will be paved with data.
Speaker Change: Multilingual and multi mobile data.
Speaker Change: Data for safety at alignment metal learning and reasoning data.
Speaker Change: Pewter use egencia and operator of data in there.
Speaker Change: Three specific data.
Speaker Change: And data from real World modeling and simulation.
Speaker Change: Now we know models performed better when supervised fine tuning data as high quality large scale highly consistent and diverse.
Speaker Change: And industry knowledge to explain where we are in capturing data is to imagine the realm of all useful data to be the size of a football.
Speaker Change: By comparison todays best performing yellow lands have been trained with datasets that are probably the size of a dime.
Speaker Change: It's even more interesting is that much of this is that captured but useful data does not even exist explicitly today, such as how to execute a multi step process using a series of websites.
Speaker Change: Or how to reach them through complex domain specific problems.
Speaker Change: We believe this likely means an even greater need for investments in our services that will be necessary to achieve the goal of hei.
Speaker Change: We intend for in the data to be at the forefront of providing these services.
Speaker Change: Moreover, we believe that innovation in hardware optimization such as.
Speaker Change: That lower the cost of compute required to train Tomorrow's L O Amazon data will enable big tech to accelerate their investments in data.
Speaker Change: We saw this kind of innovation recently from deep seek the Chinese AI research lab.
Speaker Change: They are innovative use of several existing technologies, which enabled more data to be trained with less compute.
Speaker Change: Or in fact, part and parcel of the technology Revolution previous previously popularized as Moore's law for the semiconductor industry.
Speaker Change: We expect each seeks hardware optimization techniques to be quickly absorbed by our largest customers much like other recent hardware optimization techniques that received less fanfare and future hardware optimization techniques that are inevitable.
Speaker Change: We believe that there is no viable solution for <unk>.
Speaker Change: No viable substitute excuse me for pre training data and fine tuning data to progress to hei.
Speaker Change: Techniques, such as data distillation using output of existing models to train New models May result in high performance on benchmarks, because benchmarks are inherently biased towards the past.
Speaker Change: But limiting data diversity and this way actually results in a more limited performance and ultimately causes whats referred to as model collapse.
Speaker Change: Deep seek relied heavily on data distillation.
Speaker Change: That's why in the last few weeks, we're seeing more and more of the limits of what their model can do.
Speaker Change: We're also seeing big tech companies, putting in place the technologies to effectively shut the back door to future data distillation.
Speaker Change: In addition to supplying supervised fine tuning data, we're increasingly identifying opportunities to source and transformed pre training data to solve the issues around IP infringement.
Speaker Change: One of the Big Tech companies that we signed in 2024 engaged us on pre training data in Q4, which resulted in $3 million of Q4 revenue.
Speaker Change: Tim.
Speaker Change: We're also finding expanded opportunities with big Tech companies in L O M safety and evaluation.
Speaker Change: Last month, we went to L. A trust and safety engagements with the Big Tech company that we value at approximately $3 $6 million of annualized revenue run rate.
Speaker Change: Let's talk a bit about the enterprise market.
Speaker Change: The deep sea hardware optimization that we just spoke of that makes both training and inferencing less expensive rule, we believe significantly catalyzed enterprise Gen AI adoption.
Speaker Change: This has recently been talked about as an example of the <unk> paradox. The simple idea that when technological progress makes a resource cheaper or more efficient to use it often leads to an increase in demand for that resource.
Speaker Change: We believe we are on the precipice of a rapid acceleration in enterprise adoption of generative AI.
Speaker Change: This we believe will result from hardware optimization that lowers the cost of building Gen AI solutions, and managing <unk> infrastructure as well as advancements and high quality open source models that can be fine tuned as expert agents.
Speaker Change: Innovations and orchestrating agenda ecosystems, and frontier marbles capable of performing deep research utilizing both websites and Tomorrow's agents.
Speaker Change: We're seeing that enterprise customers struggle with access to Gen AI talent.
Speaker Change: We're building technical Roadmaps to capture both operational enhancement and product innovation.
Speaker Change: And rebuilding prototypes that move into development.
Speaker Change: And as their ecosystems become more densely populated with AI agents, we anticipate that they will struggle with issues around safety interest as well.
Speaker Change: We believe our enterprise Gen. A focus presents opportunities for us to continue delivering strong revenue growth in 2026 and beyond.
Speaker Change: The strong relationships, we have with leading information companies financial services companies and other businesses have been and are expected to be a rate proofing ground for enterprise AI solutions and services.
Speaker Change: We believe we already have a line of sight to double digit growth with a number of these customers in 2025 based on forecasted Gen AI related spend.
Speaker Change: Moreover, our gen AI focused creates a clear path for reinvesting in our business with what we anticipate to be near term paybacks.
Speaker Change: Our 2025 budget calls for us to reinvest a portion of our cash from operations back into the business while at the same time exceeding our 2024 adjusted EBITDA.
Speaker Change: Our scheduled investments are largely in people spanning technology product development operations and sales. We are pleased with how successful we have been recently a recruiting select top talent from prominent technology companies and leading competitors.
Speaker Change: Our business momentum attractive as well as the opportunity to build practices that will align to the industry and technology trends that I just described.
Speaker Change: The work, we're doing with our big Tech customers on trust and safety is helping to inform our development of our automated trust and safety platform.
Speaker Change: We believe that our automated trust and safety platform will be useful to enterprises to measure how their models and agents are working to surface vulnerabilities and misalignments and to identify specific training required for continuous improvement.
Speaker Change: We're building this for the <unk> era.
Speaker Change: In which we anticipate companies will depend on a rich ecosystem agents to power their operations and products.
Speaker Change: In the last few months, we have worked hand in hand with prospective customers and partners designing functions and features we demo the platform for the Big Tech company that I spoke about earlier as having just engaged us at a $3 6 million Trust and safety program and I believe what they saw helped us seal the deal.
Speaker Change: We expect a beta release the product to select charter customers in Q2.
Speaker Change: I'll now turn the call over to <unk> to go over the financial results after which remember is a niche and I will be available to take questions from our analysts.
Speaker Change: Morris.
Speaker Change: Thank you Jack and good afternoon, everyone revenue for Q4, 'twenty, 'twenty, four which $59 2 million, reflecting a year over year increase of 137%.
This exceeded our expectations benefiting from our project delivery in the quarter for one of our new big customer.
Speaker Change: Plenty of times before as a whole we grew 96% quite.
Speaker Change: Quite a quieter adjusted gross margin was 48% representing a 4% sequential increase from the point of PARP ourselves of that hit in Q T. A plenty plenty for these.
Speaker Change: This was a solid result, given by a project for one of our new customers in the ports quiet third the deal that's all my team as well as auto.
Speaker Change: So airports and management initiatives that reduced head count and optimized cost in our seniors business.
Speaker Change: For the year adjusted gross margin declined slightly from 42% to 43%, but would have been 45% without the $3 6 million, okay cutting costs incurred in Q2 to scale the business.
Speaker Change: Adjusted EBITDA for the Port quite there it was $14 1 million or going to three 9% of revenue up from $4 3 million year over year for the year adjusted EBITDA was $30 6 million or 23% a pretzel up from nine.
Speaker Change: <unk> 9 million from 23.
Speaker Change: Our result in both quarter and the year demonstrate that stall operating leverage characteristic of our business.
Speaker Change: Net income was $10 2 million in the ports quite theyre up from $1 7 million in the same period last year.
For the year net income was $28 7 million, which was 3256% higher than 2023.
Speaker Change: We're able to utilize the benefits of accumulated net operating losses are now called in Q3 and Q4, so partially upset I talk speculation.
As a result, our effective tax rate by 22 point was approximately negative 17% without the benefit of no cook our effective tax rate would have been approximately 20%.
Speaker Change: Absent any changes sorry toxins are in London via both we expect 20 to 25 tax rate to be in the range of 22.
Speaker Change: The one 5%.
Speaker Change: Our class C and D.
Speaker Change: Q4 was $46 1 million.
Speaker Change: Yes.
Speaker Change: So I just explained pardon alien upkeep.
Speaker Change: <unk> and.
Speaker Change: Up from $13 8 million.
Speaker Change: 23.
We still have not drawn on our $30 million Wells Fargo credit facility. The three increase in Q2, I think you told before the amount available under this facility at any point in time, that's I mean based on borrowing base formula.
Speaker Change: Jack also mentioned that in 2012 to five we've planned and investing in extending our capabilities. Our internal project has the styling that strategic hires and product development expanding curiosity saw the seeds for long term growth.
Speaker Change: By Kids and forecasting perspective, we believe we can dial up reinvesting operating cash flow while at the same time aim to exceed plenty plenty for us adjusted EBITA.
Speaker Change: That's all on my side. Thank you everyone for joining today operator, please open the lines for questions.
Speaker Change: Thank you ladies and gentlemen, we will now begin the question and answer session should you have a question. Please press star followed by the one on your telephone keypad and should you wish to cancel your request. Please press star followed by Didier if.
Speaker Change: You're using a speaker phone please lift the handset before pressing.
Speaker Change: One moment. Please for your first question.
Speaker Change: Your first question comes from the line of George Sutton from Craig Hallum. Please go ahead.
Speaker Change: Yeah.
Speaker Change: Thank you Fabulous job guys. So I.
Speaker Change: I was particularly excited to see the 159% sequential growth from your seven another big Tech customers I wondered if you could just lay out the future for that group. If you would and how does that dovetail with the number of pilots that Youre seeing you mentioned seven to eight figure opportunities are those coming from those.
Speaker Change: Seven are those additional customers.
Speaker Change: Hi, George.
Speaker Change: You very much for that and great question. So the policy that we're talking about are coming from a combination of those additional big Tex.
Speaker Change: And I can think of one enterprise that we also have.
Speaker Change: A very large scale.
Speaker Change: Deal that's in and what we would refer to as a pilot.
Speaker Change: Page right now.
Speaker Change: No.
We're focused this year on big Tex in order to achieve our growth plans.
Speaker Change: We're working hard on the enterprise side as well, we're putting in place some key partnerships and key wins in key states.
Speaker Change: The abilities and and we're seeing that start to bubble up a bit in the pipeline.
Speaker Change: Yeah.
Speaker Change: So I wanted to go back to the football Dime analogy that you used in terms of where the.
Speaker Change: The current models are and and talk about your largest customer by example on it. This is really a duration question because I think one of the challenges that people have is how long will this customer be this size.
Speaker Change: Or larger can you just address it from that football dime analogy perspective.
Speaker Change: Yes, so the analogy that where we're using.
Speaker Change: And I think I can credit one of our internal data scientists with us I don't know if he got it from somewhere else, but I find it very useful so we think about.
Speaker Change: The balance of the containerization of all human knowledge as expressed or expressible potentially as data as being the size of a football.
Speaker Change: And if we hold that.
Speaker Change: Visual image in mind, we can think by comparison as the data that's been used to train today's L O lens as being the size of the Dod.
Now what does that mean that means that there's a whole lot of additional data.
Speaker Change: The models of the future are going to need to learn from to be able to function and it's something that begins to resemble overtime as agi the ability to to closely mimic the capabilities of the human and when we peel that back a bit we see lots of different things.
Speaker Change: We see expert data reasoning data multi lingual date, a multimodal data.
Speaker Change: Metal learning so learning.
Speaker Change: And expressing his data.
Speaker Change: Human beings think when they take a part of problem when they assigned components of that problem out on when they order.
Speaker Change: Their operations around solving a particular problem in the problem doesn't even have to be a particularly sophisticated one although it can be.
Speaker Change: So there's a ton of data that needs to be captured.
Speaker Change: And that needs to be addressable in order for the models to learn from it and that we believe is our opportunity or one of our opportunities its not even our only opportunity, but it's a very exciting opportunity.
Speaker Change: And given the.
Speaker Change: What you were all in we were all reading about in their recent earnings reports in terms of the uptick in.
Speaker Change: Capital spending principally for these technologies and these capabilities, we believe that where we're still in the early innings.
Speaker Change: Gotcha and then one other question.
Speaker Change: A lot of discussion relative to models being either open or closed can you talk about your opportunity as it may differ from one versus the other.
Speaker Change: Yes, sure so I think that.
Speaker Change: We've got opportunities very clearly on both sides of defense, we're working on.
Speaker Change: Open source models with customers for whom open source as a primary strategy and we're working with customers who are.
Speaker Change: Building what source models.
Speaker Change: I think.
Speaker Change: <unk> is particularly interesting because in combination with the likely declines in cost of inferencing and costs of computing cycles necessary to train models.
Speaker Change: The world of opportunity is going to open up well past today's integration strategies that for an enterprise.
Speaker Change: They're going to open up in terms of training very specific agents you can call. It small language models.
Speaker Change: We're building on top of open source models doing.
Speaker Change: Sweet.
Speaker Change: Supervise your SFC models based on that.
Speaker Change: That's a huge opportunity for us there's a.
Speaker Change: A lot that enterprise struggle with in terms of even where is their data with their.
Speaker Change: Policies around data how do they access it.
Speaker Change: Whereas a federated Golden source for the latest data.
Speaker Change: All of that is data engineering, that's going to get worked out.
Speaker Change: With our help we hope and on top of that building the models that form up their complex future egencia ecosystems. So we see opportunity all over the place right now.
Speaker Change: Alright, good stuff. Thank you very much.
Speaker Change: Thank you.
Speaker Change: Thank you and your next question comes from the line of Adam Stephen Maxim Group. Please go ahead.
Speaker Change: Okay.
Speaker Change: Okay. Congrats one business question and then a couple of financials the business Warner's.
Speaker Change: Been a lot of questions in the market with a deep seek and.
Speaker Change: Im thinking of like that maybe through influencing where they're using other AI models to kind of.
Speaker Change: Figure out the answers instead of training.
Speaker Change: And does that mean that there could potentially be less training and.
Speaker Change: I.
Speaker Change: I think you did address it but could you just kind of go into that a little more because I think there's some questions in the market.
Speaker Change: Yes, sure happy to so it is.
Speaker Change: It's well respected and well recognized among data scientists that distillation.
Speaker Change: Of data so using data from existing models to train new models creates model collapse.
Speaker Change: What happens is modeled diversity drops.
And that compromises certainly the upper limit of performance.
Speaker Change: What you observe is memorization versus true cognition.
Speaker Change: No.
Speaker Change: You can do with that cleverly in a way that maximizes how you perform on benchmarks, we call that bench maxing.
Speaker Change: And I think clearly the deep sea team.
Speaker Change: Did an amazing job at bench maxing across the diversity of benchmarks.
Speaker Change: So.
Speaker Change: Hats off to them for that but the fact remains that when you do distillation.
Speaker Change: You're usually compressing the data you're introducing a huge amount of bias into the model of your inviting model collapse and that's why you know even if you read.
The technical report from deep sea much less you know.
Speaker Change: Notes and transcripts that are available.
Speaker Change: Closed or discussions they had in China with their researchers they clearly recognize the limitations of what they've done clearly.
Speaker Change: Talk about how going forward, they're going to need to do a lot more work and a lot more investment in terms of data in order to catch up with you true performance. So.
Speaker Change: David distillation is a technique its a known technique that wasn't an innovation day.
Speaker Change: Distillation creates marvell collapse.
Speaker Change: And that's why I don't think you're going to see the people that are really driving.
Speaker Change:
Speaker Change: Toward agi in a serious way and creating the frontier models.
Speaker Change: Embracing that.
Speaker Change: As a viable technique.
Very good thank you and a couple of financial questions ill try to be quick your gross margins were 45.
Speaker Change: 2% versus 48% in the third quarter and 34, 8% in the prior year fourth quarter.
Speaker Change: You mentioned that.
Speaker Change: The reasons why one of them.
Speaker Change: I heard you guys say that it was a new pet customers something you were working on but also automation unless head count in Trinidad.
Speaker Change: I'm trying to understand is.
Speaker Change: Do you think there's potential from where it's at now.
Speaker Change: To potentially expand as we go through.
Speaker Change: 25 words, there any reasons why it was unusually a little high in the fourth quarter.
Speaker Change: And each do you want to take that.
Speaker Change: Yes.
Speaker Change: Jack.
Alan: So Alan I guess, just in terms of Q4, specifically.
Speaker Change: Now with that with that.
Alan: With that said customer we we.
Alan: There are certain projects that we're working on where we we had pretty healthy margins.
Alan: And then kind of just the mix effect without with some of our other customers. We were able to generate as you said kind of 45% kind of in Q4, as we kind of think about 2025.
Stickley: Stickley Theres always going to be some puts and takes.
Stickley: As it relates to gross margin as it relates to specific programs where with specific customers.
Stickley: We kind of want to pull.
Stickley: <unk> fully loaded basis will generally be targeting kind of around the 40% adjusted gross margin for net new opportunities.
Stickley: Which we think is a pretty healthy kind of level of margin for <unk> services company.
Stickley: Now of course, there will be opportunities as we as we continue to.
Stickley: To win new customers, we'd be hoping to just get more than that but.
Stickley: That's kind of how we're thinking about kind of net new opportunities on the margins Brian.
Stickley: That makes sense.
Stickley: Yes, that's very helpful. Thank you one last question and I know you may not answer because he didn't do it yet but yes.
Stickley: Can you help us in any way you say.
Youre going to be reinvesting, which I believe is the right thing to do.
Stickley: For long term medium term long term growth but.
Stickley: EBITDA will be up year over year is there anything you can help us with.
Stickley: In terms of qualitatively what that.
Stickley: Of being up year over year, how to think about that.
Stickley: So I think we're.
Stickley: Our plan calls for at least is to be investing primarily in people.
Stickley: Across an array of different areas and as you know I mean as I think is evident.
Stickley: <unk>.
Stickley: We prize operational excellence.
Stickley: Excellence, we're doing a lot still to tweak and automate and improve and everything else.
Stickley: So as we make investments we're going to be very careful about those we believe that there is such a rich opportunity landscape.
Stickley: We can make investments and get a very near term return on those investments.
Stickley: We see that we're able to hire some people who can be very impactful within our business.
Stickley: They love the momentum we've got right now they loved the relationship or excuse me the reputation that they here.
Stickley: We're creating in the market when they talk to our customers and they like our plant and they like our vision for what our capabilities are going to be.
Stickley: Now and into the future.
Stickley: So I think we're reluctant to fix a number in terms of what those investments will be even though in our plan. We have a number we want to be somewhat flexible.
Stickley: We want to quite possibly dial that up as we dial up forecastable growth.
Stickley:
Stickley: But.
Stickley: We're going to be disciplined about it and that's why one of the things we want to measure ourselves against and hopefully hold us to.
Stickley: Is that as we develop those investments will also be looking at.
Stickley: Adjusted EBITDA, which is our stated goal of beating last year.
Stickley: Okay, great. Thank you very much.
Speaker Change: Thank you and your next question comes from the line of handmade question Christian because nobody else financial. Please go ahead.
Speaker Change: Hi, just on the topic of Youre looking to invest in are you at capacity now with the client base you have do you need it for new projects do you need it because you have a sales funnel why do you feel like you need to expand your head count now.
Speaker Change: Sure. So I think it's helpful.
Speaker Change: To distinguish between cost of goods and SG&A.
Speaker Change: On the cost of goods side, we're able to expand in close.
Speaker Change: Proximity to opportunity.
Speaker Change: We don't need to carry a large bench of capabilities our bench of talent.
We are.
Speaker Change: We don't experience.
Speaker Change: Constraint in terms of revenue and revenue opportunity relative to cost of goods.
Speaker Change: What we do do though in cost of goods as we prepare for the next phases of growth.
Speaker Change: We.
Speaker Change: Want to make sure that we've got the management talent and technical talent and other things required in order to.
Speaker Change: Achieve our growth ambitions on that side now on the SG&A side. It's a question of ambition. It's the question well how much more do we want to do how much opportunity do we want to try.
Speaker Change: Try to seize.
Speaker Change: What are the things that we think we have.
Speaker Change: Justification and potentially winning with the relationships, we have and the brand that we have and the capabilities, we have and frankly, there's a lot that we see there so.
Speaker Change: What youre seeing when we talk about investments is a reflection of the ambition that we have or we think we can become.
Speaker Change: The people we're hiring today.
Speaker Change: Know how to do things I can hardly even understand and I love that because where we're getting deep into the technology, where we're operating in ways that go well beyond anything that we've ever done in the past and.
Speaker Change: And the work that we're doing is well received by our customers. So we're going to.
Speaker Change: We're going to keep feeding the beast, there and we'll do so as I said.
Speaker Change: In response to the last question in a.
Speaker Change: Way that.
Speaker Change: Is it as disciplined in a way that enables us to either have our cake and eat it too to both show hopefully year over year improvements in key operating metrics as well as.
Speaker Change: Growth levels like you know what.
Speaker Change: We're showing now and expansion capabilities.
Speaker Change: Okay, and then on the the pilot trials you were talking about earlier.
Speaker Change: That opportunity as far as taking business away from a competitor or competitors or is that brand new projects that you hope to win.
Speaker Change: Yeah.
Speaker Change: I think that there's probably a bit here and there that we've taken from competitors.
Speaker Change: Know that that is the case here and there.
Speaker Change: But for the most part that's not our strategy.
Speaker Change: This pie is expanding so rapidly that we're focused not on.
Speaker Change: Taking eating someone else's lunch relative to yesterday's mixing metaphors terribly yesterday's pie, but we're focused on how do we as that play expense how do we get a disproportionate share of that expansion, what do we need to be able to do.
Speaker Change: What do we need to have in place what do we need to be able to prove that.
Speaker Change: That we're seeing is adding disproportionate value relative to our competitors.
Speaker Change: Okay and then my final question is do.
Speaker Change: Do you feel like you're under or.
Speaker Change: Less stress because your cash position now or do you think because you're at a higher revenue run rate you still need a little bit more liquidity than you have now.
Speaker Change: Yes.
Speaker Change: <unk>.
Speaker Change: I think we were very well positioned we've got you see the increase in cash that we've got on our balance sheet now we havent tapped in our chapter.
Speaker Change: Our credit facility at all.
Speaker Change: We're forecasting a very significant level of free cash flow generation.
Speaker Change: And we're very targeted in terms of and very disciplined in terms of the investments we're going to be making so I think we've got what it takes and we've got what it needs.
Speaker Change: That said as you know.
Speaker Change: I'll repeat again, we're very ambitious we wanted to be in a position to seize opportunity.
Speaker Change: And as that opportunity presents.
Speaker Change: Self to us will.
Speaker Change: I hope make the right decisions.
Speaker Change: Okay. Thank you.
Speaker Change: Yeah.
Speaker Change: Thank you.
Jack: There are no further questions at this time I would now hand, the call back to Mr. Jack <unk> for any closing remarks.
Speaker Change: Operator. Thank you. So yes, Q4 was a it was a record quarter 'twenty 'twenty four was a record year.
Jack: We entered 2025 with really strong momentum.
Starting the year with guidance of 40% or more revenue growth and we'll update that as we go forward much like we did in 2024.
Jack: Our confidence is underpinned by the continuing increase we're seeing in customer demand.
Jack: We're announcing today, new wins of $24 million in annualized run rate revenue from our largest customer, bringing our total run rate to approximately $135 million with this customer.
Jack: And at the same time, you know equally exciting we grew revenue from our other seven gig <unk> by 159% sequentially and we think there's no big deal because it shows that our land and expand strategy is working.
Jack: The macro environment is working in our favor as well we believe.
Jack: The big Techs are continuing to dial up their capital commitments to AI and at the same time we're in.
Jack: Anticipating a rapid acceleration in enterprise adoption. Thanks in part to deep seeking other research labs that are optimizing hardware utilization, which then lowers entry cost for enterprise.
Jack: So the net net is we believe we're in the right place at the right time and that are potentially massive opportunity exists in front of us.
Jack: To position ourselves for continued strong growth in 2026 and beyond our plan calls for investing in the business while at the same time, hopefully growing 2025 suggested EBITDA over 2024.
Jack: The balance sheet is strong with $46 9 million in cash at year end, and an undrawn $30 million credit facility.
Jack: We've clearly got the flexibility to execute our strategy.
Jack: So again, thank you all for participating today and for being on this journey with US we're committed to nothing less than making into data one of the greatest stay I services companies out there. We will look forward to updating you on our progress as the year progresses.
Jack: Thank you.
Jack: And this concludes today's call. Thank you for participating you may all disconnect.
Jack: Yeah.
Jack: Yeah.
Jack: [music].
Jack: No.
Jack: Okay.
Jack: [music].
Jack: Okay.
Jack: Okay.
Jack: No.