Q3 2023 Innodata Inc Earnings Call

[music].

Greetings and welcome to imitate us third quarter 2023 earnings call.

This time all participants are in a listen only mode. A question and answer session will follow the formal presentation. If anyone should require operator assistance. During the conference. Please press star zero on your telephone keypad.

Please note this conference is being recorded.

I'll now turn the conference over to your host Amy <unk> General Counsel you may begin.

Thank you Paul Good afternoon, everyone. Thank you for joining us today, our speakers today are Jack Applecart CEO of ignite data and marriage and Nalley interim CFO, we'll hear from Jack first who will provide perspective about the business and then more reasonable follow with a review of our results for the third quarter.

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.

The Securities Exchange Act of 1934 as amended and section 27, a of the Securities Act of 1933 as amended forward. 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.

So even without limitation impacts, resulting from the continuing conflict between Russia, and Ukraine and her masters attack against Israel and the ensuing conflict investments in Barcelona, which models that contracts may be terminated by customers projected or committed volumes of work may not materialize pipeline.

<unk> and customer discussions, which may not materialize into work our expected volumes work, except piece of new capabilities.

We use digital data solutions 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.

Art.

Digital data solutions segment revenue concentration in all of them.

There's a number of customers potential inability to replace projects that are completed canceled or reduced our debt.

Hesitancy on content providers in our agility segment, a continued downturn in a depressed market conditions changes in external market factors, the ability and willingness of our customers and prospective customers to execute business plans that give rise to a requirements for our services and solution difficult.

T in integrating and deriving synergies from acquisitions joint ventures and strategic investments.

Undiscovered liabilities of companies and businesses that we may acquire potential impairment of the carrying of goodwill and other acquired intangible assets of companies and businesses that we acquire changes in our business or growth strategy. The.

Merchants of newer growth in existing competitors argue solved and reliance on information technology system, including potential security breaches and cyber attacks privacy breaches or data breaches that result in the unauthorized disclosure of consumer customer employee or company information.

Our service interruptions 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 Commission, including our most recent reports on forms 10-K, 10-Q, and 8-K and any amendments thereto.

We undertake 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 materially from our current expectations. Thank you I will now turn the call over to Jack.

We're very excited to be here with you today and we have lots of good news to share.

Today, we are pleased to announce third quarter revenue of $22 2 million, representing 20% year over year growth.

It's worth noting that the year over year growth was 27%.

If we back out revenue from the large social media company, which contributed 1 million in revenue with the year ago quarter, but dramatically cut spending after a significant and highly publicized management change.

We were also very pleased to announce third quarter, adjusted EBITDA of $3 2 million, representing 100% sequential quarter on quarter growth.

The $1 6 million of sequential adjusted EBITDA growth when viewed together with the $2 5 million a sequential quarter on quarter revenue growth demonstrating strong operating leverage as well as successful cost management.

Looked at year over year, we see it the same thing.

We returned $4 4 million of adjusted EBITDA growth on $3 7 million of revenue growth.

Yeah.

Third quarter growth was driven by the start of ramp up for generative AI development work.

With one of the new Big Tech customers, we announced this summer.

Correct our work with this customer to continue ramping up in the fourth quarter and into the first quarter potentially reaching a 23 to 25 million run rate at the end of the year with which to start next year.

At the very end of the quarter. We also kicked off our generative AI development program with the other new big check customer we announced this summer and we expect it will also contribute to fourth quarter revenue.

In fact, we anticipate continuing to expand revenue with both of these new customers through Q4 and in 2024.

For the fourth quarter, we are forecasting revenue of $24 5 million or more representing 26% or higher year over year growth.

Again, if we back out revenue from the large social media company, which contributed <unk> 5 million in revenue in the fourth quarter of 2022, our fourth quarter forecast would represent 30% or better year over year growth.

Since there was no revenue from the social media customer in Q1 2023, beginning in Q1 2020 for revenue from the social media customer will no longer provide a drag on year over year comparisons.

For the fourth quarter, we're forecasting adjusted EBITDA of $3 7 million or more which would be approximately 15 or more times adjusted EBITDA from the fourth quarter last year.

I'm also very pleased to announce that in September we signed a master services agreement for AI development with yet another of the world's largest tech companies the company, whose AI programs, we have been trying to break into for a year now.

Based on our research this large tech companies likely to spend several hundred million dollars Ungenerous AI data engineering services in 2024. So this win like the others that we announced this summer takes a lot of potential.

Well this relationship is at an early stage, we see huge potential in it.

As we look ahead and plan for 'twenty 'twenty, four we foresee an exciting and transformative year ahead.

We believe we have the strategy.

This momentum and customer relationships to deliver significant revenue growth and adjusted EBITDA growth.

We currently intend to provide guidance for 2020 for revenue and adjusted EBITDA growth on our Q4 call.

Our strategy for growth is twofold first we will support large technology companies building generative AI Foundation levels second we will support enterprises across a wide range of verticals that seek to integrate and fine tune generative AI models.

Let's first double click on the large tech market opportunities.

We now have master service agreements in place with five of the largest technology companies in the world under which we are providing generous today I program support.

Landing these agreements was non trivial our success at having done so I believe testifies to the strength of our value proposition and our capabilities.

With these agreements now in hand, we believe we are poised to deliver significant growth in 2024.

Over the next several years, we believe that these technology companies will be building bigger and better generative AI models.

When you listen to the large tech companies earnings calls this quarter, what emerges as an overwhelming sense. The generative AI is their number one strategic priority that is.

Their biggest investment area for 2024 and that they believe generative AI as a foundational platform shift that is just at the very beginning.

One of these companies specifically stated that it believes it will drive tens of billions of dollars of revenue over the next several years from January to pay our innovation.

The product centric large tech companies are talking about creating generative AI powered experiences across their product was transforming the way people use their products.

The infrastructure centric large tech companies are talking about deploying new and differentiated journey, which is AI surfaces and bolstering their AI infrastructure to serve their customers AI training and inferencing needs.

And both product centric and infrastructure centric large tech companies are talking about increasing capital investment into generative generous of AI as a result of the strong demand that they see.

This we believe bodes very well for us.

During the summer, we announced winning two new big five tech customers in both the program expansion and a new program with an existing big five tech customer all to help develop and train large language models.

We announced the first new big five customer win on July 18, and in July and August 29, We announced the program had been expanded.

Our program began ramping up in early August.

We anticipate that we will continue to ramp the program <unk> through Q4 and into Q1, reaching a revenue run rate on just this one customer potentially $23 million to $25 million by the end of the year with which to start next year.

We are now in discussions with this customer about potential further program expansions at potential additional programs.

We announced our second new Big five customer win on August 10.

August 22, we announced that our agreement got signed.

While our announcement well in our announcements we stated that ramp up could begin early in the fourth quarter I'm pleased to report that we were able to kick things off the tail end of the third quarter, while we had a little bit of revenue from this customer in the third quarter, we anticipate that revenue from this customer will impact our fourth quarter results more significantly.

We are now in discussions with this customer about scope of the initial program, which has the potential to be quite large as well as the other programs the.

The customer has authorized $2 5 million in spend to get US started as promised that an additional $1 5 million authorization will arrive soon and has stated that it intends to supplement these authorizations as we move forward with program expansion.

On June 27, we announced that an existing big five customer has selected us to perform AI data annotation and Oh, I'm fine tuning as a white labeled service for its cloud and platform customers and on June 14th we announced that the same customer had engaged us for itself and build program.

In the letter announcement, we stated that we anticipated potentially exceeding $8 million in revenue from this customer in 2023 up from approximately $3 million last year.

We believe that we are on track to meet or exceed this target.

Included in this year's forecast is approximately $330000 of revenue from the White label program.

Listing of six one or late stage opportunities.

We believe this white label program will contribute more significantly to 2024.

For 2024, we already have several million dollars in pipeline opportunities, including two opportunities that we value with $2 million and $1 million respectively.

It is worth noting that we believe the 2 million opportunity potentially open in exciting new market for us.

We're hoping to close both of these opportunities in Q1.

Under the White label program, we're seeing a mixture of requirements from our customers enterprise customers.

Requirements range from generative AI data pipelines to chew and three dimensional data annotation.

<unk> thought fine tuning.

L O M based search and retrieval and training LMS for multi lingual domain specific summarization and conversation.

Importantly, the program is enabling us to potentially scale and enterprise offering independent of our own sales and marketing to leverage both our customers' brand ended.

And it's significant customer reach and to gain exposure to a wide variety of early adopter generative AI use cases.

We believe this exposure will set us up well for what we believe will potentially be our largest and most significant opportunity.

For the enterprise.

I'll now talk a little bit about our enterprise opportunity and the progress we made on it in Q3.

Yes.

These are still early days in terms of enterprise adoption of generative AI, but we believe that a decade from now virtually all successful businesses will have adopted generative AI technologies into their products and operations.

To do so it will require one or more of the capabilities that we offer.

Enterprise data Sciences teams will require support to train and five in to an open source and proprietary alums to conduct specialized testing and evaluations to ensure that the Oems are helpful honest and harmless. They will also require support to implement retrieval augmented generation or Reg for sure.

The technique for harnessing enterprise data assets within LLM prompts.

Meanwhile, Enterprise line of business managers will require support to build customized generative AI models and applications.

Additionally, these line of business managers will require support to deliver the kind of business process and workflow transformation that will be possible with generative AI.

And when we identify opportunities to deliver AI enabled transformation via subscription based platform as we now have with PR workflows underwriting workflows and compliance workflows, we will enable them to subscribe to our platforms rather than having to undertake complex and expensive builds themselves.

In the third quarter, we closed three important enterprise generative AI opportunities with large companies there.

Their scope ranges from strategy to implementation.

One of the engagements we will be helping.

Oh lead leading information company create a strategic roadmap for AI L. M integration for its products and internal operations and we will be building L. O M proofs of concept.

In another we will be helping fine tuned llm's for three customer use cases pertaining to legal services in the third we will be creating datasets to training to support doctor patient interactions.

We ended Q3 with $14 8 million in cash and short term investments up from $13 7 million last quarter.

We continue to have no appreciable debt.

To support our growth and future working capital requirements, we have revolving line of credit with Wells Fargo that provides for up to $10 million of financing subject to borrowing base limitations.

I'll now turn the call over to Maurice to go over the numbers and then we'll open the line for questions. Thank you Jack Good afternoon, everyone allow me to recap our 2023 states quite as our financial results.

Revenue for the quarter ended September 30, <unk> was 22.2 million up 20% year over year. The comparator in theory. It included 1 million in revenue from the large social media company that underwent a significant management change in the second half of last quarter as a result of groups in dramatically.

Pulled back spending across the board there was no revenue from this company in the three months ended September 32000, transitory net income for the quarter ended September 32.

22023 was <unk> 4 million or one cents per basic and diluted share compared to a net loss of $3 2 million or 12 cents per basic and diluted share in the same period last year.

Revenue for the nine months ended September 32023 was $16 7 million compared to $59 6 million in the same period last year. The comparator theory and included $7 9 million in revenue from the large social media company I mentioned earlier there was no revenue from this company.

In the nine months ended September 32, 23 net loss for the nine months ended September 32023 was $2 6 million or nine cents per basic and diluted share compared to a net loss of 10 million or 37 cents per basic and diluted share in the same period last year.

Alright, adjusted EBIT that was $3 2 million in the third quarter of 2023 compared to adjusted EBIT loss of $1 2 million in the same period last year.

Adjusted EBITDA was $5 6 million for the nine months ended September 32023, compared to adjusted EBITDA loss of $3 5 million. The same period last year, our cash and cash equivalents and short term investments were appointing point 8 million at September 32023 as compared to.

$10 2 million.

Great. Thank you first thank you <unk>.

And that concludes my recap of the third quarter result, and again, thanks, everyone. I will now turn over to Paul probably are now ready for questions.

Thank you at this time, we'll be conducting a question and answer session.

If you would like to ask a question. Please press star one on your telephone keypad.

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For participants using speaker equipment, it may be necessary to pick up your handset before pressing the star keys Walter.

Once again, please press star one if you wish to ask a question.

And one moment, while we poll for questions.

Once again its star one if you wish to ask a question at any time. The first question today is coming from.

Brian Ken Slinger from Alliance Global partners.

Brian Your line. Thanks, so much.

Thanks for taking my questions.

And Jack I'm curious.

As it relates to the first big five customer that you expect may be able to reach an exit run rate of $23 million to $25 million of annual revenue.

Was there a meaningful contribution in the third quarter you highlighted it for most of the customers, but I didn't hear if it made a significant contribution and maybe if you can quantify it for the third quarter.

Sure. So you know indeed that it didn't make a significant contribution.

And.

Most of the revenue growth.

Majority of the revenue growth that you're seeing sequentially was as a result of ramping up but we are beginning to ramp up that customer.

Great.

And then just you know I think.

Your story isn't as well known right now and it may become but.

I wanted to understand how these programs are scaling.

Is it that for example, the one going to $23 million to $25 million or even.

Your second contract that you expect to generate eight compared to 3 million is it you're providing more services and they're different offerings, you're providing more testing and so you're.

Hum.

For testing more times fine tuning more in terms of volume I'm, just trying to understand what drives gale three to eight or zero getting a 25 million yes.

Yeah. So I think if we take the three to eight that's probably the best.

Example to use and then maybe we'll apply it to the 25 in the three to eight example.

We started with one program one model one initiative that they had in place.

We did very good work.

And then that would be got two or three more opportunities that we had.

We did good work there and then that enables us to further scale to start working with other programs. Other other development groups other engineering groups within the account.

And you know we refer to that as you know our our land and expand strategy. If you will.

Tough thing is to get into one of these programs.

It's a little bit like getting into Harvard that's the tough part now once you're in if you do good work.

You graduate.

Do good work you expand.

And that's what we're seeing now.

We believe that that revenue growth that we saw.

Read a predicted eight this year eight quite conceivably doubling again next year.

We believe that that same set of characteristics will apply to others of these large companies that we're now we're just getting started with the.

The fact that instead of starting with a $200000 initial engagement, we're starting with a 25 million dollar initial engagement I think bodes very well, but that expansion opportunity exists all the same.

We intend to to expand our presence we intend to go from one program to multiple programs.

And we believe that.

By doing good work, we enabled exactly that to happen.

Great and then as you're scaling these programs what are the investments you need to make.

Is it people do you need more infrastructure you try understand as revenue grows you know what what investments you have to make.

So we're making investments across the board, we're making investments in people and process and technologies.

The engineering work that we're doing.

The investments are.

Our our in all of those areas I think the important thing is that we don't foresee having.

Having to invest way ahead of the opportunity we're able to at this point, having having invested a lot in the business over the last several years and having the capabilities. We now have there's a tremendous amount of leveraging of those capabilities. So as we as we scale the programs we incrementally.

First in a way that doesn't require significant capitalized expenses.

And.

Doesn't require that we're investing in opex.

Very far ahead of.

Revenue recognition.

Okay. Thank you.

Thank you Brian good to have you on the call.

Thank you. The next question is coming from Tim Clarkson from Van Clemens, Jamie Your line of lives.

Hey, Jack Oh, good to see you or the other a couple of weeks ago.

Just wanted to ask the same questions you know I asked you in person on the call.

And you know the first question was you know historically you know are in the data has done great work and gotten projects and then the projects have ended and the stock has gone way up and then gone way down.

What's different about the kind of work Youre doing now that youre not looking to that to be a one and done project that it's going to continue to grow and scale I was using the analogy of a skyscraper and you guys are putting in the initial foundation how would you describe how this is going to build.

Yeah. So I think it's a great question Tim Firstly.

<unk>.

In the past you know we were.

We're operating in a very.

Relatively small market.

We had if in that small market a few numbers of customers. There were five large companies and on occasion, when they would build a substantial new product they would come to us to do that work, but that had a beginning middle internet and it was kind of a one off thing.

I couldn't possibly contrast more sharply.

What's going on today.

Today, we are at the crossroads of the biggest technology Revolution, I believe of our lifetimes.

Where relevant to the work the kind of work that we've done in the past is directly applicable to two large language models and generative AI.

And believe I believe that we're at the early stages of where this is going.

I think we've got the signed agreements with the major players that will enable us to to sue.

Cement that relevance and to drive that growth not just for one project as it would have been in the past.

But across multiple projects that there are only now getting out of the gate on that there are only now starting with.

Beyond those five companies that we're now working with there are other tech companies that we will continue to be pursuing and I hope landing I'm confident landing.

And beyond that there is you know all the companies that are going to be looking to use these capabilities.

And we've got a ton of experience in integrating AI into operations and into applications. So I think we've got the strategy I think we've got the.

The <unk> two to be very successful and we can leverage what we're uniquely good at to help to help drive this forward and drive a tremendous amount of growth.

Sure.

And the other key question I asked in a while as publicly as you know.

Is this you know work you're doing is it within the framework of inner Dennis competency or even more specifically so far all the clients delighted with the kind of work you've done so far.

Yeah, so far things are going very well for us as I mentioned to Brian.

It's the work that we've done that's enabled us to scale.

Dramatically and succeed as well as we have in the companies that we've been working with a bit longer than in some of these new ones.

But I believe you know will be rinsing and repeating I think that same set of capabilities that we're bringing to the table will enable us to to drive significant growth from newer relationships as well.

And you know this is the thing that's so interesting about all of this is that the capabilities that we've had historically that were unique to us that that were a value to a small <unk>.

A market the information services market.

Exactly the capabilities that are relevant to know this much larger market.

You need scalable domain expertise unique global reach you need to have.

So the technology and the processes and the DNA to create high quality consistent datasets and complex subject areas. How many companies in the world do that at scale and have the years of experience that we've got invested in exactly doing that.

So it's the perfect pivot for US and you know on top of all of that we made a really good decision about six years ago to two to invest heavily in AI and to get good at implementing models into operations until learning how to train them to perform well.

We're.

We've had a good strategy, where we've had a bit of luck I think.

Now, we're poised to reap the benefits of it.

You know when I when I look at your contracts you know one you know 5 million a quarter. Another one potentially up to 10 million a quarter. I mean is it certainly I know you're not giving.

Any kind of projections for next year, but it seems like you should be able to do over $30 million plus at some point next year just based on these contracts playing out.

Yeah I think.

You know theres a lot that we're figuring out about these relationships. There is a lot of work that's going on with our customers to figure out.

Where they need us to go and what we'll be doing.

I think we're going to be in a very good position.

Or in increasingly better position to be giving guidance I'm happy that we're giving some guidance about Q4.

I think we'll be in a position as I mentioned, a few minutes ago to give.

Can you shed some light on how 2024 is shaping up when we next several coal.

And most certainly I think a.

$30 million quarters are not at all.

Outside our reach.

The near and medium term.

Right now they are getting back to our agility I you know I had a really an excellent quarter strong profitability in EBITDA.

It looks like Youre doing just under $20 million annually, there what what would be a it all in the private market some kind of a multiple of sales would accompany like that'd be worth.

You know I really don't know the answer to that.

In terms of the value that someone would place on that specifically I know there are a couple of comps out there recently in private markets for.

You know for companies that do what agility does and evaluations where.

Based on my understanding where we're we're pretty rich.

Pretty healthy.

We're thrilled with the progress that we've made and agility.

We are having strong.

And increasingly solid quarters in terms of booking new business.

We're seeing solid retention numbers were.

We're seeing improvements in terms of the average selling price what we call the ESP.

The AI work that we've done within the agility platform you know the PR co pilot is driving new wins, it's helping bolster retention.

We've got more capabilities that are coming out.

Second half.

Of this year and maybe into next year.

In terms of leveraging AI further into those workflows being even more creative about how AI can be used by PR professionals. So it's it's fun to watch you know that business is really now hitting its stride.

Do any of your competitors have any comparable AI capability in that area.

Like agility.

Nothing like what we've got.

We havent straight great.

Great well, thanks, I'm done a good quarter.

Thank you.

Thank you. The next question is coming from Dana Bouska from Feltl.

Your line is live.

Hi, Jack.

Oh good afternoon Dana.

Congratulations on an excellent quarter.

Well. Thank you so much for that.

CRE welcome them I have a couple of questions first of all one of the things that I've been reading and the literature is that Theres, a big attempt to kind of automate a lot of the stuff that you do fully automated and I was wondering do you foresee a time when they there's going be no no.

Need for humans in the loop.

For the services you provide.

Yeah.

Yeah. So that's a complex question.

Quick answer is no I mean, we don't foresee that.

There is.

A lot of opportunity to automate aspects of of trading for classical AI, There's very limited opportunity to remove humans from the process of training large language models and they are complex.

Data science reasons for that.

Now that said you can make the work that's being done by humans much more efficient than it might otherwise be.

A lot of the technology in.

And the workflows that we've got are directly applicable to applying human <unk>.

Cognition in human capability effectively on large language models, but you can't use large language models to train other large language models. That's that's not.

An accepted practice today.

Okay. Okay. That's.

Good to know with your with the contract that you signed or the Master Service agreement you signed up with the company is expected to spend hundreds of millions of dollars.

It with a.

Yeah I services.

Well what is your roadmap strategy about going are going.

To get some of that business from that from that customer.

Well, I mean, I'm not going to leave that out.

Specificity for competitive reasons.

But yeah.

If you kind of dial it way back in the <unk>.

If it won't be any different than <unk>.

Any of the other relationships that we forged you get a foot in the door.

You put in place.

The you know the paperwork that's required so that the business can easily do business with you.

But there are no impediments that there isn't a great deal of of of work or <unk>.

Permission getting or data security audits or anything that one of their business units would need to undertake in order to work with you.

You meet as many people as you, possibly can you do you know an engagement or two and you do it very very well and where it starts to get out about the results that were obtained by working with you.

And you are you build relationships of trust based on that.

You understand where they're going you start to build into your product pipeline and your innovation.

Work that would then accommodate where they're likely to go you've tried escape to where the puck is going and.

And.

And you work hard at that.

That's basically you know the rest of it.

Okay, Okay excellent.

Hmm.

What are the announcements you made you talked about creating a golden dataset for a medical information company or.

Or like an insurance company could you tell us what it Golden Datacenters.

And what it means to your business.

Yeah. So it can mean different things in different contexts.

One of the reasons that you might use a golden dataset is to benchmark large language model.

So you would create a golden dataset of how you would want to see the model responding if it's tuned properly too.

Aligned with human values and to align with the business case.

Alright, and what does that mean.

For your business that you've been able to you know that youre able to do that or you.

We're working with this customer to do that.

Well I think it is one of very many opportunities that we've got to be relevant.

For engineering teams, who are building large language models, it's one of many things thats required to.

<unk> successfully.

Train and.

And launch a foundational oh.

Hey.

Foundation model and generative AI.

So there is fine tuning required as reward model of industry enforcement learning you know there are a lot of different components of things that are required. There is work that you would do for evaluating the capabilities of the model.

You'd be reevaluating it from a trust and safety perspective.

In the context of that.

Golden datasets can be important.

Okay. Okay.

Excellent and then one last question when do you start tackling the your enterprise.

Marketplace.

How are you anticipating that you're going to go about doing that or you're going to have to like add more salespeople more consultants well how are you thinking about tackling that.

Yes, a couple of ways.

We're very excited about the white label program that we've not referred to several times.

Because it gives us the ability to scale and gain to scale, our business and gain exposure to enterprise use cases.

Independent of sales and marketing that's a huge opportunity that gives us a lot of.

Competitive advantage I believe.

Beyond that I think.

The enterprise opportunity will be driven by direct sales for the most part although we also do see another couple of channel opportunities that we're exploring as well.

Okay.

Thank you that's it for me.

Thank you Dana.

Thank you and once again its star one if you wish to ask a question.

The next question is a follow up from Brian can singer from Alliance Global Partners, Brian Your line of lives.

Okay, great. Thanks for taking my follow up.

Clearly your offerings that address large language models.

Notation, even with the enterprises is growing.

Growing or if not will be growing very fast.

But if I'm not mistaken there are significant revenue base that predates fish that you were talking about before that was a little bit more lumpy correct me if I'm wrong it doesn't still exists so.

Is that business still stable declining or growing as we think about next year are for our own sake.

So the from a sales.

<unk> execution perspective.

The work that we're hunting right now primarily is.

The work that we're doing with large tech companies and the AI enablement work that we're looking to do for enterprises.

We're very focused on that now that runs across the enterprises run across multiple verticals.

One of the.

One of the capabilities that we're able to leverage the relationships that we've got with enterprises. So we've worked over the years with very many enterprises in.

Business information sector, we've worked with enterprises in the financial services sector, we've worked with enterprises in life insurance.

And all of these are companies that are trying to figure out actively how do these technologies apply to their businesses and how do they apply to their products.

So you're absolutely right, Brian that we've got hooks into the companies who are actively thinking about this and the capabilities that we're bringing back to those customers.

Capabilities that have.

We've developed an AI, they're very receptive to.

We talked about how we.

We announced three enterprise deals that we closed this quarter or Q3.

And a couple of those were you know were customers that we've done things with years ago, having nothing to do with AI or very little to do with AI managed service capabilities.

But now we're going back to them with a different value proposition.

That there.

Very much receptive to and embracing.

Great.

Thank you so much.

Thank you. The next question is coming from Bruce Galloway from Galloway capital Bruce Your line is live.

Hey, Jack congratulations on being a visionary in this area.

Obviously, you are the first mover advantage and since Jan JBT and Microsoft.

Kind of like a tsunami in this area and I am sure there has been a major shift.

Of capital into this area through the venture community and also the private equity community along with all the existing technology companies that are going to be chasing it.

It services for January of AI.

Can you talk a little bit about the competition and where you are with regard to the competition and maybe talk about.

Some of the valley.

Evaluations in that segment of the marketplace to.

To give us an idea of what your company could be worth.

Sure so well.

First Bruce Thank you for your kind words, I don't know that I deserve.

Those are certainly all of them, but thank you for that.

We're competing against are you know several companies in and will probably be competing with more companies as we move forward in this area. There's a lot of activity here.

You know the predictions that analysts released for growth and generative AI related services are huge over 100% CAGR for the next 10 years. So you don't.

Naturally that will as you're saying attract a lot of interest and a lot of money.

There are companies that we know.

Our our about our size or somewhat larger who have enormous.

Valuations.

We think we compete favorably with them.

And Ah you know.

Our focus is to keep doing what we're doing to do it well and you know as you've seen from the results we're driving.

Aggressive growth, we're lining up more and more relationships of trust.

We're demonstrating that you can can can grow aggressively and be profitable at the same time.

And close these major deals, which I think is kind of a hat trick that I'm very proud of.

Yes, there are some some big valuations out there I think our valuation will take care of itself as long as we keep executing.

What are some of the valuations that are being done out there.

Like a price to revenue basis.

We don't have perfect knowledge of that.

We're aware of some you know.

Some of our company for example that has a better.

We're told the $250 million topline with.

<unk>.

Evaluation of about $7 billion, a couple of years ago.

Again.

Not an investment banker I don't want to get.

I don't want to go well outside my wheelhouse here.

But we're aware of those kinds of private market valuations and.

Yeah, I think we just stay very focused on execution and keep doing what we're doing and I think we've got a strategy now that enables growth in lots of interesting ways.

And you.

No we can do a really good job by shareholders by staying focused.

Okay. Good job thanks.

Thank you.

Thank you. The next question is coming from Tim <unk> from White Pine capital Tim Your line is live.

Hi, Jack Congratulations on your quarter, a nice job.

Question.

Two quick questions. One is could you talk a little bit about gross margins and what you expect over kind of.

The near term.

Yeah.

Sure happy to do so in terms of gross margins I think the way to.

Think about.

Kind of the expansion economics of our business is too.

Look at the two flavors of business, we have fundamentally there's a services and solutions business.

And then there's a platform business and our consolidated gross margin will be.

Or the.

Factoring in both of those together.

Our adjusted gross margin on the services and solutions side is probably.

Within a range of 37% to 42%.

And our adjusted gross margin on the platform side of the business is probably like you know high 60, 68, 69% to about 75%.

A modeling perspective.

Yeah.

And then you know I think you've seen that in combination with the work that we've done on carefully managing cost structure.

We were doing very well when you look at the incremental.

Adjusted EBITDA that were throwing off as we scale.

Yes, I guess I was looking at direct operating costs over revenues.

And coming to a lower number but I figured it's somewhere in the adjustment.

Certainly the revenue growth.

Adjusted EBITA looks fantastic, but maybe I can take it offline just to understand how to think about adjusting gross margins.

Or looking at direct operating costs over revenue growth a little there.

So now we're happy to take you through that basically what we're adjusting for us.

Stock based compensation and DNA.

So there's an add back there okay.

That would be the add back and you'll get leverage on that add back because that won't necessarily keep increasing at the same rate as revenue.

Okay I understand thank you.

Last question was on the Microsoft call. The other day and I couldn't help but notice that they're using co pilot also you.

You trademark that with PR co pilot, how does how does that work where they're using co pilot around large language models also.

Well I think it's a really good name.

I think it's a great name I just kind of wondering how did they talk to you before they started using that name or are they all white labeling that from you or.

Yeah.

They're not in and that certainly isn't our biggest concern I think it's a great description further way.

It abuse technologies can be used to augment the work that people do.

Can you provide that kind of augmented real time real live assistance.

I think the exciting thing is those technologies certainly are our PR copilot is just going to get better and better and better and more and more personalized so.

I'm happy to be picky name that other people think as well too right.

Benefit for us and that Theres, certainly no lawsuits that we're initiating.

Just last quick question I was thinking about the question earlier or we've been tracking for years and you had some great projects over the years and I was wondering if you could talk a little bit about the history and what you've learned on some of these projects and how it relates to your current business kind of tying that.

Lineage or heritage all together for us.

Yes happy to so so you know what we've made a business over over the years is creating large scale high quality data for companies where.

Errors or not.

Are not welcomed where errors or not tolerated.

The tolerance for any mistakes is virtually nonexistent. So we've developed technology around that.

Processes around that and DNA around that.

And we've done this in lots of different domains by which I mean.

Subject areas medical health care legal regulatory tax financial and insurance.

On and on and on.

Now.

The thing to know about large language models in AI fundamentally is the key ingredient beyond compute for training and inferencing.

<unk> T ingredient is data and the higher the quality of data the better performing be AI will big.

So we're able to take that fundamental core competency that we have and pivot off of that very directly for creating high quality.

That's why you know I like to think that all of the work that we've done over now decades has been kind of training camp for you know it's like training for the Olympics that we are in the Olympics and we're bringing a lot of very relevant training to the table.

Yeah. That's some of the criticism I've heard on large language models is that the if the data sets not right.

The answer might sound logical, but it could be false.

How how do you ensure.

Or could you talk a little bit more about the skill set of putting together the right data set for the right model to make sure that you're getting the right output.

Yeah, so so theres a little bit of danger, there and conflating 222 problems. One is that the model just doesn't work very well for language isn't helpful. The.

You know, it's kind of cognitive ability is in there.

And things like that the other related issue is hallucination and you don't necessarily solve hallucination through.

The quality of data you solved hallucination.

In some respects through.

The kind of work that Youre doing on performance evaluation and.

Trust and safety work and the kinds of data that you're feeding into it but it's just not a data quality problem.

Got it great well, thanks, I'll jump back in the queue.

Thank you.

We have reached the end of our question and answer session and I will now turn the call over to Jack <unk> for closing remarks.

Great.

Well, thank you operator, and thank you everybody for your great questions.

I'll recap a little bit we now have.

Hard fought for Master services agreements with five of the 10 largest technology companies in the world for generative AI development, we're super excited about that we're.

We're expecting these companies to spend billions of dollars over the next several years for training and fine tuning generative AI models.

We're now or soon expecting to be ramping up engagements with all of these companies.

In Q3, we got a taste of the growth that we believe is in store and we anticipate further growth in Q4 and continuing into 2024.

As we said, we're guiding to $24 5 million or more of revenue in Q4.

Today, we also announce having signed an agreement with yet another of the world's largest tech companies, adding to our already rich roster of opportunities and with the significant incremental adjusted EBITDA gains we're delivering we're demonstrating that we have what it takes to grow aggressively.

But to grow aggressively and profitably as we harness the.

The opportunity that's in front of us and the tailwind that we're we're we're benefited by.

My team and I are energized by what we've accomplished by the number of new major accounts, we now have to deliver growth.

And the magnitude of the market opportunity that's in front of US. We believe we're now just at the early stages of exploiting these market opportunities and we believe that these market opportunities are themselves at their early stages. So.

Very exciting and again. Thank you all will be very much looking forward to our next call with you.

Thank you. This does conclude today's conference you may disconnect. Your lines at this time. Thank you for your participation.