Q4 2022 Innodata Inc Earnings Call
Good afternoon, ladies and gentlemen, thank you for standing by today's conference call will begin soon once again, thank you for your patience.
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Greetings welcome to <unk> fourth quarter and fiscal year 2022 earnings call. At this time all participants are in a listen only mode. A question and answer session will follow the formal presentation.
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Now turn the conference over to your host Amy address you may begin.
Thank you John and good afternoon, everyone. Thank you for joining US today, our speakers today are Jack Apple heart to CERP and our data and there is just an early interim CFO , we'll hear from Jack first who will provide perspective about the business and then the rates will follow.
With a review of our results for the fourth whether in the 12 months ended December 31, 2022, well then take your questions first let me qualify the forward looking statements that are made during the call. These statements are being made pursuant to the safe Harbor provisions of section 21 E. After Securities exchange.
<unk> Act of 1934 as amended.
<unk> 27, a of the Securities Act of 1933 as amended.
We're looking statements include without limitation any statement that may predict forecast indicate or imply future results performance or achievements. These statements are based on management's current expectations assumptions and estimates and are subject to a number of risks and uncertainties.
Cheese, including without limitation, the expected or potential effects of novel Coronavirus, COVID-19, pandemic and the responses of government. The general global population, our customers and the company. There are two impacts resulting from the rapidly evolving conflict between Russia and Ukraine.
Investments in large language models that contracts may be terminated by customers projected or committed volumes of work may not materialize.
And opportunities and customer discussions, which may not materialize and she'll work our expected volumes of work acceptance of our new capabilities continuing digital T. This progression segment reliance on project based work and the primarily at will nature of such contracts and the ability of these customers to reduce.
Delay or cancel projects the likelihood of continued development of the markets, particularly new and emerging markets that our services and solutions support continuing digital data solutions segment revenue concentration in a limited number of customers.
And the ability to replace projects that are completed canceled or reduced our dependency on content content providers in our agility segment, a continued downturn in or depressed market conditions, whether as a result of the COVID-19 pandemic or otherwise changes in external market factors.
Do you.
The ability and willingness of our customers and prospective customers to execute this.
This plant effective rise to requirements for our services and solutions difficulty in integrating and deriving synergies from acquisitions joint ventures, and strategic investments potential undiscovered liabilities of companies and businesses that we may acquire potential impairments of the carrying value of goodwill and other <unk>.
Prior intangible assets of companies and businesses that we may acquire changes in our business our growth strategy, the emergence of new or growth in existing competitors argue stuff in reliance on information technology systems, including potential security breaches and cyber attacks privacy breaches are.
Data breaches that result in the unauthorized disclosure of consumer customers employee or company information, our surface interaction and various other competitive and technological factors and other risks and uncertainties indicated from time to time in our filings with the securities and exchange.
<unk>, including our most recent reports on Form 10-K, 10-Q, and 8-K and any amendments thereto. We undertakes no obligation to update forward looking information or to announce revisions to any forward looking statements, except as required by the federal securities laws and actual results could differ.
Really from our current expectations. Thank you I will now turn the call over to Jack Thank you Amy and good afternoon everybody.
Thank you for joining our call.
Today I'm going to talk briefly about our Q4 and year end results and then I'm going to spend some time discussing recent acceleration in AI investment by large technology companies and large language models, coinciding with a open AI is fourth quarter release of its large language model called chat GPT.
And how we believe and the data is quite well positioned to capitalize on this increased investment.
So first our results.
For revenue was $19 4 million, a 5% increase over the prior quarter, which annualized is roughly two of 2000 2022 or 22% growth rate.
We posted positive adjusted EBITDA of approximately $250000 in the quarter, which was a positive swing of $1 5 million from Q3.
This significant improvement resulted primarily from our September October cost containment and efficiency initiatives.
The benefits of these initiatives will be fully reflected in our first quarter 2023 results.
We ended the year with a healthy balance sheet, no appreciable debt and $10 3 million in cash and short term investments on the balance sheet.
In 2022 overall, we grew revenues, 13%. Despite the significant revenue decline from our large social media customer that underwent significant internal disruption in the second half of the year, but that we believe may normalize this year.
Let's now shift to the recent substantial uptick we are seeing in our market activity.
As most everyone now knows in late Q4 open AI unveiled chat GPT. This.
AI large language model has since gone viral capturing popular imaginations for its ability to right to generate computer code to converse at what seems like human or even superhuman levels of intelligence.
We believe the release of chat GPT has been broadly seen as a watershed event potentially heralding a fundamental advancement in the way AI can drive changes in business communication processes and productivity.
Our market intelligence indicates that many large tech companies are accelerating their AI investments as they compete for domination in building and commercializing large language models and that an arms race of sorts isn't that forming.
We believe that the significant investment that will likely result from this competition could dramatically accelerates the performance of these large language models.
As a result of this dramatic increase in performance, we expect almost every industry will face fundamental reinvention.
We believe that the opportunity for in the data and all of this is significant.
And that isn't that it is now upon us.
We believe our opportunity is actually threefold first to help large technology companies, both existing customers and new customers compete in this large language model arms race.
Second to help businesses incorporate large language models into their products and operations and third to integrate these technologies into our own platforms.
Let's take each of these in turn starting with what I just laid out is our first opportunity, helping technology companies, both existing customers and new customers compete in the large language model arms race.
Well chat GPT and a host of lesser known but equally impressive large language models are for sure amazing.
Our view is that it's still early days.
We believe these large language models have room for significant improvements in output quality and the languages. They serve in the domains they support and in terms of safety.
These are all challenges that we believe we can help with.
We expect to help by collecting large scale real world data for training.
By creating high quality synthetic data when real world data.
Training is hard to come by.
By Annotating training data and by providing a reinforcement learning from human feedback or R. L. H F to fine tune model performance and eliminate hallucinations, which is the tendency of these models to make things up on the fly.
In addition, we expect to help by minimizing the risk that models generate unsafe. We're biased results and we expect to help by hyper training generalized models for specialized domains.
High quality data is at the root of addressing all of these challenges and this is and has been in a data is bread and butter specialty for 30 years.
We believe that the arms race to which I'm, referring has likely already begun.
In just the past few weeks it seems.
Activity for us is dramatically searched.
We are now either expanding work with beginning work with or discussing working with four of the five largest technology companies in the world.
I'm going to share some examples of the surge in activity we've seen in just the past few weeks.
The major cloud provider, whose AI needs. We began serving 24 months ago engaged us to help them build a new large scale generative model for images.
We started the initial phase of this just this week.
In addition, the customer asked US just last week to kickoff a pilot to support their generative AI large language model development we.
Started the pilot this week.
We have the same customer also in the last few weeks, we expanded our synthetic data program to support its large language model development.
We believe high quality since the synthetic data is likely to be a key ingredient to performing to a high performing large language models of the future.
Synthetic data is entirely new data that we generate through our machine assisted process to match real world data and maintain all of the statistical properties of real World data, which is especially useful for capturing rare cohorts and outliers of interest synthetic data is also helpful to correct for data bias to improved algorithm.
<unk> furnace and to avoid having to retrain proprietary or confidential data.
We started working with synthetic David back in 2022, and we've been continuously improving our capabilities and technologies for some fit synthetic data creation since then.
With this customer we've gone from surfing just one of their product lines to now being firmly engaged with three product lines and we are in pilots with three additional private clients.
Also in the past couple of weeks with another of the world's largest tech companies. This one a company that would be a new customer for us we've gotten a verbal commitments to assist them on projects relating to large language models.
They have told us that they are in the final stages of putting in place a statement of work.
There can be no assurance that the S. W is put in place based on our current estimations and assumptions value of this program could potentially approach approximately $1.8 million per year run rate in its initial phases and could ramp up to approximately $6 million per year as it gains momentum.
In addition, two weeks ago, one of the world's largest social media companies another potential new customer for us reached out to discuss how we might potentially support its large scale model development.
It has been referred to us by one of our existing customers, who apparently said that we could be helpful in unlocking value.
Unlocking scale and by bringing our consultative approach to a partnership.
We believe that the opportunities that I've, just mentioned individually and in the aggregate are potentially very large.
I want to underscore that several of these our pipeline opportunities and at various stages of pipeline from early stage to late stage pipeline opportunities are inherently difficult to forecast and often do not close.
That said.
I've worked with them here in support of two beliefs.
The first belief that there is building momentum among big Tech companies for AI innovation generally enlarge language model specifically.
And the second belief that in the data's reputation for high quality work with high quality outcomes is becoming firmly instantiated in a dynamic market that is viewing us as a potential partner in one of our generation's greatest innovations.
Now, let's shift to our second significant market opportunity.
We believe that our second significant market opportunity is to help businesses harnessed. The power of these foundational generative AI models.
Most enterprises have tasks that generative AI can make easier.
As the technology improves and we expect it will we believe that businesses will see incorporating the technology is a must have rather than a nice to have.
Analysts are predicting that this year. The most forward thinking business leaders will be actively putting time and money into re imagine their products service delivery and operations based on what AI can do for them leading to widespread deployments over 'twenty 'twenty four and 2025.
What we're also hearing, especially from Cto's is that their biggest roadblock to deploying AI is finding the right engineers and data scientists to help them get there.
We believe our opportunity will be to do just that to help them get there.
We anticipate that this will take the form of fine tuning existing pre trained large language models on specific tasks within specific domains, bringing.
Bringing expertise and prompt engineering, the art of prompting large language models to produce the appropriate results and.
In helping with large language model application integration.
Early in the first quarter of 2023, a large financial technology company expanded scope with us to leverage our proprietary AI models more fully and reengineer their technology for the cloud to drive operational efficiencies.
Our proprietary AI engine Golden Gate uses the same underlying encoder decoder transformer neural network architecture as J P T.
GPT is trained broadly Golden gate is trained narrowly on specific tasks and domains.
Experiment with coupling GPT and Golden Gate and this seems to result in even higher orders of performance.
This is the third scope expansion, we've had with this company over the course of the past six months again, providing further validation of our land and expense strategy.
We believe we're a third opportunity is to harness GPT and other large language models in our own AI industry platforms.
Just last month, we announced PR co pilot the new module within our agility PR platform that combines proprietary in a data technology and GPT to enable communications professionals to generate first drafts with press releases and media outreach in record time.
With our release of PR Copilot, we became we believe the PR industry's first integrated platform to incorporate large language Marvell technology.
The implementation was significant for any data and we received the support of Writeup in PR weekly for it.
The startup named Jasper voltage Unicorn status when it implemented something very similar to PR copilot for creating blogs and social media postings.
Their efforts got them at $125 million series, a round on a healthy $1 5 billion dollar valuation.
With respect to our agility platform, we're seeing positive momentum in key performance indicators, which we think PR co pilot and our newly integrated social media listening product will help to further accelerate.
In Q4 agility platform sales grew 6% over Q3, which annualized is to a roughly 26% growth rate.
In 2022 overall, our direct sales new logo bookings increased by 83% year over year and our direct sales net retention increased to 100%.
In 2022 overall, approximately 83% of our agility revenue came from direct sales and 17% of our revenue came from channel partners.
In Q4, our conversion from demo to win indirect sales increased to 33% up from approximately 18% at the beginning of the year.
We believe the notion that customers, who use US love US is also very much apparent in our Senate X platform.
Sydney Index grew by 71% in 2022 with a net retention of 168%.
We announced in Q4 that one of our largest <unk> customers have expanded its recurring revenue program with us.
And the announcement, we stated that expansion was valued at approximately 600 $600000, but we now believe the value of the expansion is actually closer to $1 $2 million.
This is now our second largest index customer with an estimated annual recovering revenue base of $2 $3 million.
This year, we will be focused on product development to expand our addressable market for medical data extraction, we've got new products currently being evaluated by charter customers in disability claims processing personal injury claims processing and long term care claims processing as well as in clinical medical clinical medical and <unk>.
Data annotation and fully automated life underwriting.
Integrated AI will be a feature in all of these products.
We are more enthusiastic than ever about our market opportunity and the intrinsic value of our business.
In our last call. We said, we anticipate expanding our adjusted EBITDA to $10 billion or more in 2023 and at the same time, capturing significant growth opportunities.
We believe the activity we are now seeing in our markets will likely enable us to achieve this and potentially more.
I'll now turn the call over to <unk> to go over the numbers and then we'll open the line for some questions.
Thank you Jack Good afternoon, everyone, let me recap the quiet quarter and fiscal year financial results our revenue for the quieter and their December 31, 2022 was $19 5 million compared to revenue of $19 2 million.
Period last year.
Net loss quite a quiet there and then December 31st 1992, 2 million or seven cents per basic and diluted share compared to a net loss of $1 2 million or of course cents per basic and diluted share in the same period last year.
The total revenue for the year ended December 31st 90 to 92 was $79 million up 13% from revenue of $69 8 million in 2021 net loss for the year ended December 31st 2022 is 12 million or what are your four cents per basic and diluted share compared.
So a net loss of $12 7 million or <unk> per basic and diluted share in 2021.
Adjusted EBITDA was 2 million in the poor quarter of 2022 compared to adjusted EBITDA.
3 million in the same period last year adjusted EBIT loss of $3 2 million for the year ended December 31st 2022, compared to adjusted EBITDA of 3 million in 2021.
Our cash and cash equivalents and short term investment or a $10 3 million at December 31st 2022, consisting of cash and cash equivalent of $9 8 million and short term investment of <unk>.
$5 million.
In April <unk> 9 million at December 31st 2021, consisting of cash and cash equivalents.
So thanks, everyone again, we are now ready for questions.
Thank you.
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One moment, while we poll for questions.
The first question comes from Tim Clarkson with Van Clemens Tim.
Tim Please proceed.
Hi, Jack apologize if you hear noise in the background, we had a major snowstorm in Minneapolis in the snow is coming off our buildings saw anyhow.
First question I have is.
What exactly is that.
Technology experience that makes it a data.
If.
Successful it at.
Moving forward artificial intelligence and in these chat bots.
Sure Tim it's.
Not limited to Chatbot artificial intelligence people believe and I firmly believe is at a kind of a fundamental inflection point, we're now seeing.
What kinds of technologies that people who've drempt about probably since the 19 fifties.
And when you think about building these technologies and thinking about what goes into them. It's not programming in the traditional sense. It's data it's high quality data and data that can help to address some of the fundamental problems that these technologies have.
They need to improve their output quality babies to improve languages, they're supporting it needs to be customized for particular domains they need to improve.
We think of the safety.
Kinds of responses to fix the kinds of things that they tell us.
So well what needs to be done for that things that need to be done or the things fundamentally that we've done for a very long time very very successfully for some of the largest.
<unk> companies out there.
When we were being retained by <unk>.
Large engagements we've had in the past things like Apple.
What we were doing for them was fundamentally building large quality data and high quality data, but for products and for publishing here. We're building. It because data is the appropriate programming language of AI and the programming language of large language models.
Right right and what typically are the gross margins on the revenue that you're getting from this are these high high gross margin products.
I think from a gross margin perspective, I would continue to expect a range of gross margins from our different capabilities.
In the services sector I think.
Mid <unk> to mid Forty's.
Gross margins are achievable and they'll get better overtime.
As we introduce automation and technology they tend to drift higher.
When we're starting up new projects, they tend to drift a little bit lower on the platform side. They.
They are higher than that.
Incremental gross margins, especially can be.
Substantial.
And as we build scale and start to scale on our fixed costs, we can start to see the kinds of.
Gross margins that will emerge from from those types of business models.
Right right well just one last comment I, you know I've been all excited about in a data lately and the analogy I use is it.
Now what's happened with artificial intelligence is as before with sort of like a da Vinci seeing of a picture of an airplane.
But it's one thing to see a picture of an airplane. So another one to see one fly Bayou and Gulf from Minneapolis to New York and when you actually see this artificial intelligence stuff work.
No longer have to be sold on the value I mean, it's it's magical so that's.
That's for me. It's that's the difference as people are really excited about the end product.
And emotion is what drives our.
You know ultimately decision, making and real excitement behind us so with that I'm done. Thanks.
Thank you Tim.
The next question comes from at Danaher, Bhaskar with Feltl and company. Please proceed.
Hi, Jack how are you today.
Dana I'm doing great. Thank you welcome to the call outcome, yes.
Thank you for taking my questions.
My first question is with your new PR.
PR co pilot.
You talked about your own technology and I was just wondering if.
Your technology is more than just accessing an API at open AI.
So it is I mean, it's.
Basically what we're doing and we've got very exciting roadmap. We really believe we have only just got started with <unk>.
CECI P T.
But what we're doing is we're combining an API with prompt engineering that we've done behind our UI and behind the scenes.
And in the future, where we're going to be doing is we're going to be enriching the training data to more specifically performed within the domain.
We've also done other things in terms of that and we will be doing other things in order to further enriched experience. So when you take the two fundamental use cases, we're addressing one for writing press releases in one four.
For writing media outreach.
We're looking at what goes on in someone's head when they're looking to do either one of those things.
What connections are they making where are they having to go and research and built into our product and built into our underlying data model. Our lots of connections that were able to harvest and bring then into.
Into the prompts in order to create a more precise.
Level of output.
So it's very much a combination phase things now one of the reasons Ive.
<unk> said for several reasons, but one of the things that it's enabling us to do.
Is to create a lot of value for PR, but at the same time learn a lot about how do you integrate these technologies to create a superior customer experience and we're able to bring that that experience and turn to the work that we're doing for for other customers. So it's a.
It's great fun and it really is a new frontier.
Okay.
That sounds wonderful I was wondering if you are going to be able to apply your.
Co pilot technology to other other industries or other companies.
Our other applications. So we're certainly talking to other companies about this we're looking at some opportunities to apply large language models within our Senate X platform. That's kind of early days, though so I wouldn't encourage you not to expect anything out of that.
Very quickly.
We think the roadmap go for PR Copilot has fairly extensive we've really only begun down that path. So we're very excited about that.
Excellent.
With agility.
<unk>.
Where are you.
<unk> breakeven for that it's going to be.
So I don't think we put out a number.
Relative to that but what we've said is that we think we are going to be getting that business too.
To become.
Adjusted EBITDA positive business in the first half of the year.
Okay excellent.
And.
In the past you would give out projections for the first quarter and I don't know if I missed it or not but do you have any type of.
Projection in revenue growth.
What youre thinking for the first quarter.
So we've decided not to this year for the most part we're probably not going to provide forward looking guidance only because of the level of activity that's going on in the business.
So substantial and coming on so strong there.
Being able to reduce these things too.
Casts and know when something is going to close and know what it's going to look like and how it is going to wrap up.
Almost impossible so the likelihood that we would be wrong and maybe even significantly wrong is pretty substantial.
Therefore, we've gone the other direction, which is kind of.
Which I think is materially disclosing here's what's going on in the business, Here's what's coming our way.
We are now working with four of the five largest technology companies, who are fundamentally driving what will probably be the innovation of our lifetimes.
No doubt look back on it.
As that.
We're partnering with them, we're involved in that opportunity views coming our way.
So long story short, we're not we're not.
We're going to stay out of the guidance business right now, but we're going to try to disclose.
What we're doing and level of activity that we're seeing.
Okay.
We anticipate it will be a growth year.
Yes, we're very much.
Very much focused on growth so yes.
The easy answer to that.
Okay excellent alright, thank you.
Once again, if you have a question or a comment please press star one on your Touchtone phone once again Thats Star. One if you have a question or comments. The next question comes from Marco Petroni with MG Capital Management. Please proceed.
Hey, Jack how are you.
Marco Hi, how are you.
Good.
Couple of questions one.
Everybody has AI and machine learning algorithms.
Put them to different users, but is there any company out there that you know that combines that with the ability that you have on the data side with regards to organize and collected.
Overlaying synthetic data on top of that is there anybody out there, including the big guys that can do that.
Well I think there are I think there are a couple of companies that are doing some things that are similar to us, though not very many.
We've kind of got a view of the world that we can do two things well.
And we think that there is like a virtuous circle.
Forums, when we do the three things well first as AI data preparation.
Helping large companies accelerate.
Their ability to innovate in AI by doing the things that we do on the data side.
Second thing is we're then helping deploy those models and integrate them into People's businesses. So we're helping build the models and then we're helping integrate the models and then thirdly, we have our own platforms and we're learning the hard way, we're eating our own dog food and we're figuring out how to do it for ourselves first so we then develop the expertise to bring to.
Both the data collection.
How do you collect data in a way that results in high performing models and then on the model deployment, how do you best deploy models in legacy workflows on legacy systems.
What are the opportunities for reinvention that you can.
Bring to bear.
The GPT is great to go in but you know I have had experiences where I put the same data and you give them different answers.
Obviously that can be used within a company.
You guys do you guys have the same capabilities of open AI in terms of creating those type of chats gpt's within an organization.
Specifically for an organization. So for example, there their call centers or internally.
Being able to use that to interact amongst employees as well as customers.
Yes, so to be essential architecture behind <unk>.
<unk> is an architecture that is also behind our proprietary Golden Gate technology.
Now do we have the same ability to two <unk>.
Stand up something that performs the way that that one does in a generalized way absolutely not.
We don't have the budgets hundreds of millions of dollars was likely spent on.
On getting trained to the level that it's been trained on Theres, a tremendous amount of data that could support in.
To create the billions in hundreds of billions of parameters that drive that model.
A tremendous amount of cloud processing went into that.
We cannot do that but what we can do and what's the future of the way. These things will work as we can build on those.
Training that we can customize them.
We can use what's called reinforcement learning from human feedback in order to train customized domain customized models with private side data to enable them to perform better thats really going to be the future of this so we will see.
The big companies with large language models proprietary to them large language models, we will help them build those but we won't be able to fund those ourselves, but then what we'll be able to do is customize them and build upon them in order to create.
Business outcomes for people.
It wasn't just one last question.
You guys are trading at $200 million roughly two times revenue.
What is the company going to do going forward now that I mean, obviously.
It.
As everywhere what is the company going to do to market, our stock basically and get out there I know earnings and revenue are great, but to get out there and do that what do you have planned in the next coming months and quarters.
So I think I think the most important thing we can do for our shareholders and of course I'm prominence among our shareholders.
Is to continue to do the things that we're doing.
The fact that we are in four out of five of the largest technology companies, helping to develop what will be.
It transformative technology that is still in its infancy and will need a lot of work over the next several years.
But we've gotten there and we're doing that.
I think is huge that we've gotten there and are doing that without having to go out into the markets and dilute our equity and raised a ton of that.
As you know.
I think it's.
I think it's an impressive feat now.
How do we better promote that I think the first thing starts with execution and then what follows from that is.
Lots of conversations with people, who I'm, hoping we'll be attracted to the execution that we're bringing to bear and of course looking at some of the techniques that people use.
Conferences.
Outreach and talking to analysts and all of those things, but fundamentally we're going to be about execution.
No absolutely, but I mean, I've been a shareholder for two years.
Nobody really knows about us every other co.
The company is trading at.
510, 15 multiple on revenue, we're trading at two times and going forward, we have the potential of growing 30 plus percent. It seems like we're pretty undervalued here compared.
To the sample, but thank you.
Thanks Marco.
Okay. The next question comes from Craig Samuels with Samuels Capital Management. Please proceed.
Hey, Jack how are you.
Hey, Greg how are you well thanks.
Pretty good thank you.
Back in several quarters ago, you talked about.
Our total number of sales reps for both agility and then.
Service solutions side.
Where do you stand today with the numbers of sales reps.
So on the services solutions side on the AI side, we're about at the same number that we have.
<unk> shared.
We've taken down the number quite a bit on the agility side.
And a couple of things went into that decision first of which was in the beginning of the year, we were having a hard time retaining people first specifically in one of the sales offices that we put up.
It was.
There is a labor shortage that was pretty well known we were in Austin, Texas, where a lot of SaaS companies, where they were overpaying as far as I'm concerned for talent and we didn't want to play that game.
So what we decided instead was let's be good stewards of capital, let's not let's not play the game of overpaying for talent.
Let's instead.
Worked with a smaller number and we've had great success retaining very.
Very talented salespeople in.
And others of our offices.
Let's retain them, let's work on it let's let's build a sales organization that has very much a data driven approach to sales.
And to optimizing our customer experience and build from there.
I think thats.
Proving to be.
The right decision as.
As we look out.
<unk>.
<unk>, we kind of see what's going on now we see.
New logo booking up 83% year over year, our net retention.
From the nineties up to 100% now.
Significant performance improvement relative to the number of demos that we do that end up in closed sales going from like 18% beginning of the year to 33% now.
With that we will I believe see acceleration and growth and it's always easier to throw logs on a fire that's burning struggling so that's.
That's kind of where we are.
Right. So I don't remember the last numbers that you had.
Can you share them for services.
Going back in time I seem to remember it was like six or seven and on the agility side.
Got a target of $1 10, and the last numbers that I have.
And 67 zone.
That's been a little while can you actually sure.
Sure I think what we said was we had.
Nine folks quota bearing executives and services solutions area and then we had a combination of.
About 90 people 42 quota bearing people and agility and another 37 <unk>.
We've in agility.
We have reshuffled those numbers pretty considerably in terms of the mix in the workflows and we brought that number down quite a bit I don't have the current number to share with you.
Happy to do that.
Off the call when I go get that but we brought that down and we're getting the performance off of that smaller cohort which is.
At the end of the day, what it's all about.
Right and then on the on the.
Nine.
Service sales reps.
I recall from again, the prior two years ago.
Craig Sorry, I think he dropped off.
One moment I'll reconnect Craig.
Okay.
Okay.
Greg can you hear us.
I can hear you are you there okay. Your line is live.
Not sure what happened, but yeah, hi, Craig onshore happening.
I had asked about staff productivity and.
I seem to remember about a million and a half.
Dollar quota per service AI sales rep.
That still consistent with where you guys are today or has that number gone up or down.
Yes, so I think we put that out there with a average the in the services and solutions area of the quarters are actually derived from the account assignments so depending upon the.
The accounts that people are working on there they can be fairly significantly different from that that can be much higher than that.
An entry level person who's kind of.
Building is account base can be lower than that.
Got it.
Then also Nvidia.
Had some news regarding the datacenter, providing computer power for AI.
And just wondering if that helps you or if that's competitive.
No I think it's very much supportive of the value proposition.
No.
I was on their call.
<unk> bid there.
What we said on the call and.
I think the way they're viewing the opportunity is very much the way we're viewing the opportunity they're looking at it from a different perspective. They are looking at it from a perspective of enabling it from a processor side.
We're looking at it from a perspective of enabling it with data and.
These are two sides of the same coin as far as I'm concerned.
Yes.
Exactly what I thought.
I wanted to hear you.
Confirm that and then lastly.
Would you expect your gross margins.
To increase over the next 12 to 36 months.
While there'll be a greater software component or will it still be.
Heavily weighted towards services.
I think it depends.
And kind of what happens.
Given the activity that we're now seeing.
Great significance.
I think we will continue.
Accessible at closing the opportunities that are before us I think we're going to continue to see a very heavy weighting toward solutions and services from a consolidated margin perspective.
I'm willing to live with that problem.
<unk>.
Right, so that means that when the and the.
Below 40.
Not necessarily I think that.
As we start to.
Execute the plan.
We will be able to move above 40% overtime.
But probably still below 50.
Again.
Sure.
<unk> to be seen what we're able to deliver on the on the platform side, but if the opportunity is as large as we are hoping it is on the solutions side.
I think it will wait toward toward that.
Yes.
Good keep up the good work and look forward to continuing to monitor your progress over time.
Thanks, Thank you.
We have reached the end of the question and answer session and I will now turn the call over to Jack for closing remarks.
Thank you operator, so yeah ill quickly recap.
We're seeing very recent acceleration in AI investment by large tech companies.
It seems to be coinciding with the opening <unk> releases chat GPT.
Now either expanding work with or beginning work with or discussing starting work with four of the five largest tech companies in the world and much of what is under discussion has to do with building and improving large language models.
Very excited about where we are with these companies and excited about where we are with a host of similarly impressive companies across other domains.
<unk>.
Even though forecasting exact close states remains challenging we think we're in the right place at the right time to to ride this wave.
We're seeing positive trends across our other business segments as well.
<unk> growth last year was huge it's well positioned to expand in this market this year.
As agility.
Supported by what we believe was a very successful release of PR copilot.
We continue to make great strides in win rate net retention bookings all of which are of course, leading indicators of accelerating growth. So.
Very excited to be here today very excited with the news that we're sharing today and.
Thank you all for participating in this call, we'll look forward to our next call with you.
This concludes today's conference and you may disconnect. Your lines at this time. Thank you for your participation.