Q4 2023 Innodata Inc Earnings Call

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Operator: Greetings. Welcome to Innodata's fourth quarter and fiscal year 2023 earnings call. At this time, all participants are in a listen-only mode.

<unk> welcome to enter data is fourthquarter in fiscal year 2000 twenty-three earnings call. At this time, all participants are gonna listen only mode of question and answer session will follow the formula presentation.

Operator: A question and answer session will follow the formal presentation. If one should require operator assistance during a conference, please press star zero on your telephone. Please note, this conference is. I'll turn the conference over to you, Amy?

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 will now turn the conference over to your host Amy address you may begin.

Amy: You may begin. Thank you, John. Good afternoon, everyone.

Thank you John Good afternoon, everyone. Thank you for joining us today, our speaker today are Jack Apple C E O and data.

Amy: Thank you for joining us today. Our speakers today are Jack Abelhoff, CEO of Innodata, and Mariz Espinelli, Interim CFO. We'll hear from Jack first, who will provide perspective on the business, and then Mariz will follow with a review of our results for the fourth quarter and the 12 months ended December 31, 2023. We'll then take your questions.

Spinelli Insurances D S L or hear from Jack first he'll provide perspective about the business.

Will follow with a review of our results for the fourth whether in the 12 months ended December 31, 2023, well then take your questions before we get started I'd like to remind everyone that during this call we will be making forward looking statements.

Amy: Before we get started, I'd like to remind everyone that during this call, we will be making forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, assumptions, and estimates, and are subject to risks and uncertainties. Actual results could differ materially from those contemplated by these forward-looking statements. Factors that could cause these results to differ materially are set forth in today's earnings press release, in the risk factor section of our Form 10-K, Form 10-Q, and other reports and filings with the Securities and Exchange Commission. We undertake no obligation to update forward-looking information.

You have a prediction is projections or other statements about future events.

Based on current expectations assumptions, an estimate and are subject to risks and uncertainties actual results could differ materially from those contemplated by these forward looking statements factors that could cost is for yourself to differ materially are set forth in today's earnings press release, and the risk factor section of our Forum 10.

K or 10-Q and other reports in filings with the Securities and Exchange Commission, we undertake no obligation to update forward looking information. In addition, during this call we may discuss or the non-GAAP financial measures and their SEC filings, which are posted on our website you will find additional disclosures regarding.

Jeff: 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 reconciliations of these measures with comparable GAAP measures. Thank you. I'll now turn the call over to Jeff. Good afternoon, everybody.

These non-GAAP financial measures, including reconciliations of these measures with comparable GAAP measures. Thank you I'll now turn the call over to Jack.

Good afternoon everybody.

Jack Abelhoff: We're very excited to be here with you today as we have a lot of good news to share. We are pleased to announce fourth quarter 2023 revenues of $26.1 million, representing 35% year-over-year growth and 18% sequential, exceeding our guidance of $24.5 million by 6.5% as a result of strong customer demand for generative AI services and our ability to ramp up quickly to meet customer demand. In 2023, overall, we grew revenues by 10%. Now, it's worth noting that our Q4 2023 year-over-year revenue growth was 39% versus 35%, and our year-over-year revenue growth was 23% versus 10% if we back out revenue from the large social media company that went through a highly publicized take-private in 2022, in conjunction with which it terminated our services, as well as services from many This customer contributed $8.5 million in revenue in 2022 and $0.5 million in revenue in Q4 of 2022. Beginning in Q1 2024, revenue from this customer will no longer provide a drag on year-over-year comparisons. We're also very pleased to announce fourth quarter adjusted EBITDA of $4.3 million, exceeding our guidance of $3.7 million by 16%.

Very excited to be here with you today is we have a lot of good news to share.

We are pleased to announce fourth quarter, 2023 revenue 26.1 million, representing 35% year over year growth and 18% sequential growth.

We exceeded our guidance of 24.5 million by 6.5% as a result of strong customer demand for general <unk> services.

And our ability to ramp up quickly to meet customer demand.

In 2023 overall revenues 10%.

It's worth noting that our queue for 2023 year old and your revenue growth was 39% versus 35%.

Your over your revenue growth was 23% versus 10% if we back out revenue from the large social media company that went through a highly publicized kick private in 2022.

In conjunction with Richard terminated our services as well as services for many of its other vendors and laid off 80 per cent and stuff.

Each customer contributed 8.5 million in revenue in 20 22.5 movie in revenue in Q4 of 2022.

Beginning in Q1 2024 revenue from this customer will no longer provide a drag on your over your comparisons.

We're also very pleased to announce fourthquarter adjusted EBITDA was 4.3 million exceeding our guidance of 3.7.

By 16%.

Jack Abelhoff: Growth in Q4 was driven primarily by the ramp-up of generative AI development work for one of the big five tech companies we signed in mid-2023, and it also benefited from the start of generative AI development programs with another of the big tech customers we announced late last summer. In late Q4, the first customer I mentioned signed a three-year deal with us for our current initial program with an approximate value of $23 million per year for each of 2024, 2025, and 2026, for $69 million for the three years based on the not-to-exceed value of the statement of work. We're very proud of this achievement, which came with customer kudos for the work that we've done and expressions of interest in expanding the partnership further.

Growth in queue for.

Primarily by wrap up of gender Tuesday, I development work for what is the big five Tech companies resigned mid 2023.

I'd also benefited by the start of gender Tuesday, I developed a program with another of the Big Tech customers screen is late last summer.

Q for the first customer I mentioned and signed a three year deal with US for our current initial program with an approximate value of 23 million per year for each of 2024, 2025, and 2026 469 million for the three years.

Based on the not to exceed value statement is worse.

We're very proud of just the cheese.

It came with customer kudos for the work that we've done and expressions of interest in expanding partnership further.

Jack Abelhoff: That said, and as a cautionary note, investors should understand that there are a number of ways under the SOW that the customer could terminate early or reduce spend if it shows. We believe the quality of our services will always be the key to enduring customer relationships, not the stated value or term of a contract. We're off to a strong start in 2024.

That's it and there's a cautionary note investors should understand that there are a number of ways under the S. O W. That's the customer could terminate early or reduce spend if it shows too.

We believe the quality of our services will always be the key to enduring customer relationships not the stated value or ter of a contract.

We're off to a strong start enjoying the 24 re entered the year with Masters service agreements in place with five of the so called magnificent seven technology companies.

Jack Abelhoff: We entered the year with master service agreements in place with five of the so-called magnificent seven technology companies. With two of these companies, we are now solidly underway. A third also contributed to Q4 growth with a more significant ramp-up from this customer starting this month. We're optimistic we will grow revenues with all three of these customers in 2024. With the remaining two of the five MAG-7 customers, we've barely gotten out of the gate, but we're optimistic about making significant inroads this year.

With two of these companies were now solidly underway.

A third also contributed to queue for growth with a more significant ramp up from this customer starting this month.

We're optimistic we will grow revenues with all three of these customers in 22 and explore.

The remaining two of the five Meg seven customers, we've barely gotten out of the gate, but we're optimistic about making significant inroads this year.

Jack Abelhoff: We're also in conversations with several additional companies, including some of the most prominent leaders in generative AI today. We believe we have the strategy, business momentum, and customer relationships to deliver significant revenue growth in 2024. We will stick to our annual growth target of 20% in 2024 with the intention of overachieving this.

We're also in conversations with several additional companies, including some of the most prominent leaders <unk> today.

We believe we have the strategy.

Does this momentum and customer relationships to deliver significant revenue growth in 2024.

We will stick to our annual growth target of 20.

20% and 2024 with the intention of over achieving this.

Jack Abelhoff: In 2024, we will target two broad markets. The first is big tech companies that are building generative AI foundation models and, we believe, are likely to spend significantly on generative AI development. For these big tech companies, we provide a range of services they require to support their Gen A programs. One of these services is the Creation of an Instruction Data System. You can think of instruction datasets as the programming language used to fine-tune large language models.

In 2024, we will target too broad markets.

The first is big Tech companies that are building churches, a foundation models and reboot leave are likely to spend significantly on <unk> development.

For these big Tech companies, we provide a range of services they require to support their Janet I programs.

One of the services is the creation of instruction data sets you.

You can think of instruction datasets as the programming used to find two large language models.

Jack Abelhoff: Fine-tuning with instruction datasets is what enables the models to understand prompts, to accept instructions, to converse, to apparently reason, and to perform the myriad of incredible feats that many of us have now experienced. We will also be providing reinforcement learning and reward modeling, services which are critical to provide the guardrails against toxic bias and harmful responses. In addition, we are also involved in model assessment and benchmarking, helping ensure that models meet performance, risk, and emerging regulatory requirements. Based on my conversations with several abuse companies, as well as the public remarks they have made, we believe they are likely to spend hundreds of millions of dollars each year on these services. This spend is separate from, and in addition to, their spend on data science and computation, the other essential ingredients of high-performance large language models.

Fine tuning with instruction datasets is where the neighbors the models to understand trumps to accept instruction to converse to apparently reason and to perform a myriad of incredible feats that many of US is now experience.

We will also be providing reinforcement learning and reward modeling services, which are critical to provide the guard rail against toxic bias and harmful responses.

In addition, you are also involved in model assessment and benchmarking, helping ensure that models meet performance risk and emerging regulatory requirements.

Basically my conversations with several reviews companies as well as public remarks. They have made we believe there are likely to spend hundreds of millions of dollars each year in the services.

To spend is separate from and in addition to their spend a data science and compute the other essential ingredients of high performing large language models.

Jack Abelhoff: Our second target market is enterprises across a wide range of verticals that seek to integrate and fine-tune generative AI models. However, these are still early days in terms of enterprise adoption of generative AI. We believe that a decade from now, virtually all businesses will have adopted generative AI technologies into their products and operations. For enterprises, our offerings include business process management, in which we re-engineer workflows with AI and LLMs and perform the work on an ongoing managed service basis. We also offer strategic technology consulting, where we work with customers to define roadmaps for AI and LLM integration into both operations and products, and build prototypes and proofs of concept. We also fine-tune models, both in isolation and as part of larger systems that incorporate other technologies.

Our second target market is enterprises across a wide range of vertical that seek to integrate and fine tune gender today I'm models.

Is that these are still early days in terms of enterprise adoption of gender today, well, we believe that a decade for virtually all businesses will have adopted gender today I I technologies into their products and operations.

For enterprises are offerings include business process management.

Which we re engineered workflows with a I L M and perform the work on an ongoing managed service basis. We also offer strategic technology consulting, where we work with customers to define roadmaps for a I M. L. M integration into both operations in products and build prototypes and proofs of concept.

We also fine tuned models broke in isolation and as part of larger systems that incorporate other technologies.

Jack Abelhoff: For enterprises, we are capable of going from soup to nuts, everything from initial consulting to model selection to fine-tuning, deployment, and integration, as well as testing and evaluations to ensure that the LLMs are helpful, honest, and harmful. Also, for enterprises, we offer subscription-based platforms and industry solutions that encapsulate AI, both our own models and leading third-party models. Much the way data is at the heart of programming, like the work we do for big tech, data is similarly critical to enterprise deployment. Enterprise use cases tend to be highly specific and targeted, requiring models that are trained with industry-specific or domain-specific data, or that require significant prompt engineering efforts and in-context learning, utilizing carefully curated and organized company data.

Four enterprises, you're capable of going soup to nuts everything from initial consulting to model selection to fine tuning deployment and integration as well as testing and evaluations to ensure that <unk> or helpful honest harmless.

Also for enterprises, <unk> subscription based platforms and industry solutions that encapsulated i-i, both our own models and leaving third party models.

Much the way data is at the heart of programming like what can we do for Big Tech data is similarly critical to enterprise deployments.

Enterprise use cases tend to be highly specific and targeted requiring models that are trained with industry specific or domain specific data or that requires significant prompt engineering efforts and in context learning utilizing carefully curated and organized company data.

Jack Abelhoff: The bottom line here is that data engineering is important for the big tech companies building generative AI foundation models and the enterprises adopting these technologies. Data engineering has been our focus for the past two decades, and we believe we are quite good at it. I'm going to take a few minutes now to respond to some questions I've been asked by investors recently. Number 1, Several investors have asked whether we currently anticipate needing to raise additional equities. The answer is no; we do not currently anticipate needing to raise additional equity.

The bottom line here is the data engineering is important for the Big Tech companies building generous <unk> Foundation models and the enterprise's adopting these technologies.

Data engineering has been our focus for the past two decades, and we believe we are quite good at it.

I'm Gonna take a few minutes to respond to some questions I've been asked by investors recently.

Number one.

Several investors to best whether it be currently anticipate needing to raise additional equity.

The answer is no we do not currently anticipate needing to raise additional equity.

Jack Abelhoff: We ended Q4 with $13.8 million in cash and short-term investments. Slightly down from $14.8 million last quarter, but that was largely due to timing, as we had $2.4 million in cash receipts from major customers collected right after the new year, and we generated over $4 million of adjusted EBITDA in Q4 alone. Nonetheless, to support our growth and future working capital requirements, we have a revolving line of credit with Wells Fargo that provides up to $10 million of financing, 100% of which was available under our borrowing base as of the end of Q4. We have not yet drawn down on the Wells Fargo line.

We ended Q4 with 13.8 million in cash and short term investments slightly down from 14.8 million last quarter, but that was largely due to Tommy as we had 2.5 2.4 million in cash receipts from major customers collected right after the new year.

And we generated over 4 million of adjusted EBITDA in queue for a loan.

Nonetheless to support our growth in future working capital requirements, we have a revolving line of credit with Wells Fargo that provides up to 10, <unk> 100 per cent of which was available under a borrowing base as of the end of the queue for.

We have not yet rundown on the Wells Fargo lines, we anticipate generating enough cash from operations in 2024 to fund our capital needs without having to draw it down on the Wells Fargo facility.

Jack Abelhoff: We anticipate generating enough cash from operations in 2024 to fund our capital needs without having to draw down on the Wells Fargo facility. Number two, several investors have asked why we have no chief financial officer. Well, in a sense, we actually have four Chief Technology Officers, or at least their equivalents, each of whom manages specific technology areas. We have a Ph. D. in computer science and A.I.

Number two.

Several investors to ask why do we have no chief financial Officer.

Well in a sense, we actually have four chief financial excuse me Chief technology officers.

Or at least their equivalents each of which manages specific technology area.

We have a ph D in computer science and AI you heads are AI Lab's research team and data science teams.

Jack Abelhoff: who heads our A.I. lab's research team and data science. We have an SVP of engineering overseeing product and platform engineering. We have another VP focused on software development and product evolution for our agility product, and we have a Chief Information Security Officer who heads security and infrastructure. Under these leaders, we have close to 300 developers, architects, infrastructure managers, and data scientists.

Have an S V P of engineering.

Overseeing products and plot for mentioned here.

We have another V P focused on software development product evolution for agility product and we have a chief information Security officer, who had security and infrastructure.

Under these leaders so we have close to 300 developers architects infrastructure managers and data scientists <unk>.

Jack Abelhoff: We have found that this structure best supports the breadth and scale of our business. Investors have asked us to share our recent spending on software and product development, and I asked why we do not separately disclose it to comment on whether we have a significant spend on cloud infrastructure. So there are three separate questions there, and I'll address each one. In terms of our spending across software and product development, over the last five years, we spent about $26 million, which peak in 2022 at 8.9 million and came down to 6.4 million in 2023. However, since roughly 80% of our business is managed services, we do not view the aggregate spending across these areas as a focal point for investors.

<unk> this structure best supports the breadth and scale of our business.

Investors Sebastian to share our recent spending I'm software and product developed.

And I've asked why we do not separately disclose it to comment on whether we have the signature can spin and cloud infrastructure.

So there are three separate questions are there and I'll address each.

74, spending request software and product development over the last five years, we spent about $26 million.

This peaked in 2022 at $8.9 million and came down to $6.4 million in 2023.

However, since roughly 80% of our business is managed services, we do not view the aggregate spending across these areas as a focal point for investors.

Jack Abelhoff: In terms of cloud, we spend a couple of million dollars per year on software, infrastructure, and data hosting. It is our big tech customers, not us, that spend massively on GPUs for training foundation models. Other investors have asked us how they should think about our comps. Specifically, they asked whether our comps are companies like OpenAI, Google, and Meta, and whether they should compare our R&D spend and cloud compute spend to those companies. These companies are absolutely not our competitors.

In terms of cloud we spent a couple of million dollars per year, mostly for software infrastructure and data.

It is our big <unk> customers not us spend massively on G. P used for training Foundation models.

Other investors have asked just how they should think about our comps specifically they ask whether our com Sir companies like open a Google and <unk>, whether they should compare our R&D spend in cloud computing spend to these companies.

These companies are absolutely not our comps.

Jack Abelhoff: Rather, these companies constitute part of our target market. However, we are not in their business, and to state the obvious, we are not of similar skill. Layers in this market are building foundational models, and we are providing services to this market that help them on that journey. Therefore, we do not believe that comparing our R&D spend and cloud compute spend to theirs is especially useful; review our competition as companies focused on AI data engineering services to this market, like Scale AI and others, and companies more broadly focused on technology services, but also focused on AI data engineering, like Accenture and Cognizant. Another question I've gotten is, how do we manage to pivot to AI without having to raise substantial capital? There are essentially three reasons we were able to pivot to AI without having to raise capital.

Rather these companies constitute part of our chocolate market <unk>.

We are not in their business and to state the obvious we're not of similar scale.

Players in this market or building foundation models, and we are providing services to the cheapest market that helped him on that journey.

Therefore, we do not believe that comparing our R&D spent in cloud computing benches, heiresses, especially useful.

We view our competition is companies focused on AI data engineering services to this market like scale, a I and others and companies more broadly focused on technology services, but also focused on the AI data engineering like Accenture and cognizant.

Another question I've gotten this has to be managed to <unk> without having to raise substantial capital.

First initially three reasons, we were able to <unk> to a without having to raise capital.

Jack Abelhoff: The first reason, which we believe is by far the most important, is that the massive spend we've read about being required to build foundation models is incurred by our large tech customers, not by us. Our customers are deploying extensive amounts of capital for cloud compute, for data science, and for data engineering. Three crucial ingredients to an LLM, if you will.

The first reason, which we believe is by far the most important.

That's a massive spending read about being required to build foundation models is incurred by our large tech hub customers not by us.

Our customers are deploying extensive amounts of capital for cloud computing for data science enter data engineering.

<unk> if you will.

Jack Abelhoff: We provide the kinds of data engineering services they need, and providing data engineering does not require that we separately incur compute costs. The second reason we were able to transition to AI data engineering without incurring massive upfront costs is that we have been a data engineering company for over 20 years, and we were able to repurpose a lot of what we already had in place, including management, resources, facilities, and technologies to serve the AI use case. The third reason is that when we began exploring AI back in 2016 and developing our Golden Gate infrastructure, we incurred manageable investment. From a data perspective, because we were already employing large teams of resources doing customer work, we did not have to incur incremental additional costs for humans in the loop. We simply had to re-architect our operator workbenches and create the right data lakes. The objectives we initially set for the models we built were to enable us to reduce costs associated with maintaining rules-based data processing technology.

We provide the kinds of data engineering services, they need and providing data engineering does not require that we separately incur computer costs.

The second reason, we were able to transition to a I data engineering without incurring massive upfront costs is that we have been a data engineering company for over 20 years, and we were able to repurpose a lot of what we already had in place, including management resources facilities and technologies to serve.

Use cases.

The third reason is that when we began exploring AI back in 2016 and developing our Golden gate infrastructure, we incurred manageable investment.

From a data perspective, because we were already employing large teams of resources doing customer work, we did not have to incur incremental additional costs for humans and Luke.

We simply had to re architect or operator, workbenches and to create the right data lakes.

The objective screen. Additionally, set for the models, we built where to enable us to reduce costs associated with maintaining rules based data processing technologies.

Jack Abelhoff: We were not seeking to automate the work of humans but to augment it. Over the years, GoldenGate, as one of our proprietary platforms, became, we believe, state-of-the-art at things like entity extraction, Data Categorization, and Document Zoning, all important aspects of what we do. The technology is deployed in customer deployments and within our own platforms and yields great results. That said, Golden Gate is not a chat GPT. You can't converse with it or ask it to write poetry.

We were not seeking to automate the work of humans, but to augment it.

Over the years Golden Gate is one of our proprietary platforms became we believe state of the art at things like entity extraction.

Date of carrier categorization and documents zoning.

All important aspects of what we do.

The technology is deployed in customer customer deployments and within our own platforms and you'll is great results.

That said Golden Gate is not CECI P. T. You can converse with it or ask you to write poetry.

Jack Abelhoff: GoldenGate has 50 million parameters, while Chats GPT is reputed to have 1.7 trillion parameters. Nevertheless, GoldenGate demonstrates that AI can be trained to perform specific tasks very well without incurring massive spending, that AI deployments leveraging open source algorithms and models can be within reach for many enterprises for industry-specific data sets, and that for business implementations, especially, data engineering is more important than sheer model size as a predictor of performance. The question I got recently is how revenue per employee compares in your different lines of business. The answer is that revenue per employee is lowest in our managed services business, while it is multiple times higher in our AI data engineering scaled services. Regardless, we target an adjusted gross margin of 35 to 37 percent across these two business lines, and we believe gross margin is the better metric to track.

Golden Gate has 50 million parameters will check CPT is reputed to have 1.7 trillion parameters.

Nevertheless, Golden Gate demonstrates that a it can be trained to perform specific tasks very well without incurring massive spending.

That AI deployments leveraging open source algorithms of models can be within reach for many enterprises for <unk> specific datasets.

And that for business implementations, especially data engineering is more important than sheer model size as a predictor of performance.

Question I got recently, it's how does revenue per employee compare and your different lines of business.

The answer is that revenue per employee is lowest at our managed services business wallet as a multiple times higher in our a I data engineering skilled services.

Regardless, we target and adjusted gross margin of 35% to 37% across these two business lines and we believe gross margin is the better metric to track.

Jack Abelhoff: In our software business, our target gross margin is anticipated to be about 73% this year, and we intend to target a consolidated adjusted gross margin of between 40 and 43%. The final question I've gotten several times recently and that I want to respond to on today's call is, is agility now profitable? The answer is yes. In this quarter, Agility posted adjusted EBITDA of $1.2 million.

And our software business are chartered gross margin is anticipated to be about 73%. This year and we intend to target a consolidated adjusted gross margin of between 40 and 43 per cent.

The final question I've gotten several times recently that I want to respond to on today's call is this agility now profitable.

The answer is yes.

In this quarter agility posted adjusted EBITDA of $1.2 million.

Mariz Espinelli: This was a 69% sequential increase over Q3. We think we executed the agility business very well in 2023, growing at 15% in a difficult macro environment. It had a strong adjusted gross margin of 69% for 2023 as a whole and 74% in Q4. We also love what we've done with the product. We believe we've taken a leadership position as the first end-to-end public relations and media intelligence platform to integrate generative AI. I'll now turn the call over to Mariz to go through the numbers, and then we'll open the line for some questions. Thank you, Jack. Good afternoon, everyone.

This was a 69% sequential increase over Q3.

We think we executed the agility business very well in 2023 growing at 15% in a difficult macro environment.

It had a strong adjusted gross margin of 69% over 2023, as a whole and 74% in Q4.

We also love what we've done with the product.

Believe you've taken leadership position is the first and two in public relations and media intelligence platform to integrate general <unk>.

Oh now turn the call over to <unk> to go through the numbers and then we'll open the line for some questions.

Turnkey Jack Good afternoon, everyone allow me to recap I quite quite there in fiscal year 1993 with salt.

Mariz Espinelli: Allow me to recap our fourth quarter and fiscal year 2023 results. Revenue for the quarter ended December 31st, 2023 was $26.1 million, up 35% from revenue of $19.4 million in the same period last year. The comparative period included $0.5 million in revenue from a large social media company that underwent a significant management change in the second half of last year, as a result of which it dramatically pulled back spending across the board.

That'd be quite the ended December 31st 1993 less than to 6.1 million updated my per cent <unk> 19.4 million.

The same period last year.

Confided period included point $5 million in revenue from delight social media company.

The significance management changing the second half what's nice Q S.

<unk> pull back spending across the board.

Mariz Espinelli: There was no revenue from this company in the 3 months ended December 31st, 2023. Net income for the quarter ended December 31st, 2023 was $1.7 million or $0.06 for basic share and $0.05 for diluted share compared to a net loss of $2,000,000 or $0.07 for basic and diluted share in the same period last year. Total revenue for the year ended December 31st, 2023 was $86.8 million, up 10% from revenue of $79 million in 2022. The comparative period included $8.5 million in revenue from the large social media company referenced above. There was no revenue from this company in 2023.

There was no wedding you from this company in the three months ended December 31st 1993.

Net income quite the quite the ended December 31st 1993, with 1.7 million or six.

Six cents with basic <unk> compared to a net loss of 2 million or seven cents for basic and then with a chair in the same period last year.

Total that'd be new for that you ended December 31st 1993 with 86.8 million.

10 per cent combating you up 79 million in 2022.

<unk> unlimited 8.5 million in revenue from delights, Social media company Redfin said that.

There was no way of doing it from this company in 2023 <unk>.

Mariz Espinelli: Net loss for the year ended December 31, 2023 was $0.9 million, or $0.03 per basic and diluted share, compared to a net loss of $12 million, or $0.44 per basic and diluted share, in 2022. Adjusted EBITDA was $4.3 million in the fourth quarter of 2023 compared to adjusted EBITDA of $0.2 million in the same period last year. Adjusted EBITDA was $9.9 million for the year ended December 31, 2023, compared to an adjusted EBITDA loss of $3.3 million in 2022. Our cash and cash equivalents, and short-term investments were $13.8 million at December 31st, 2023 and $10.3 million at December 31st, 2021. Now, before I turn you on for questions, like Jack, I also have gotten some questions from investors recently that I promised to respond to on today's call. The first question was about why we keep cash overseas. The reason we keep cash overseas is to cover operating expenses in this location. We do not plan to repatriate this fund, nor do we foresee the need.

<unk> for the year ended December 31st 1923, with point 9 million three cents per basic and then with the carrier.

Alright next month I'll spell Malian 44 cents.

Basic and then repeat sir and tend to tend to to.

<unk> <unk> <unk> <unk> <unk> <unk> can I get 23 compared to like Justin EBITDA point 2 million in the same period last year.

<unk> that was 9.9 million <unk> and then December 31st 1923, <unk> digested the loss of 3.3 million in 2022.

Alright, <unk> cash equivalent in short term investments with 13.8 million at December 31st 1923, and 10.2 million at December 31st 1992.

No <unk> gone for questions like Yeah can I also have gotten some questions from indefinitely recently that that time is to respond to answer these calls.

The first question was about why do you keep costs overseas.

The reason that he keep cash overseas, it's the corporate operating expenses and dislocation Ethernet plan, So <unk> <unk> <unk> <unk>.

<unk> didn't need to.

Mariz Espinelli: Further, another question was about cost plus transfer pricing agreements with our offshore subsidiaries. Companies that have revenue in, say, North America or Europe but have offshore delivery centers in countries like India and the Philippines put in place what's called transport pricing. Transfer Pricing Arrangement. This is to satisfy the arm's-length transaction principle. Under a transfer pricing arrangement, a percentage of revenue is allocated to the delivery center. The percentage allocated is often determined by statute or regulation in the foreign country.

Alright, there is another question about cost less transfer pricing agreement with <unk> up sorry subsidiaries <unk>.

Company <unk> in say, North America, or Europe, but tab, Oxford centre in countries like India, and the Philippines put in place what's called transfer pricing.

Transfer pricing arrangement. This is dissatisfied I'm fullington section principle.

I'm gonna transfer pricing <unk> <unk> <unk> <unk>, it's allocated to the delivery center the percentage allocated to authenticate mean by statute or regulation in a foreign country.

Mariz Espinelli: We understand that the reason the foreign country does this is to make sure that there are profits at the local level for it to tax. However, when a consolidated enterprise is losing money and would not otherwise have to pay taxes, it unfortunately ends up having to pay taxes offshore. Obviously, paying taxes when you're losing money is not a good thing, and it's referred to as tax leakage.

We understand that the reason the coin country's destiny is to make sure that their property. It's at the local level for each attack.

However, when it comes to alleviate the 10th at practice loosing money and would not otherwise have to pay taxes, either unfortunately ends up having to pay taxes off shore.

Obviously, taking taxes and you're loosing money spent a good paint and <unk>, but even in this situation the taxi <unk> insignificant, but it's just the money be safe bye operating up sorry, this business model listen to any comedy clubs in any industry and not to make the in the data.

Mariz Espinelli: But even in this situation, the tax we pay is insignificant versus the money we save by operating offshore. This business model is very common across many industries and not unique to Innodata. The last question that I've gotten is whether there is any structural reason that Innodata would be expected to lose more money as it generates more revenue. The answer to this is absolutely not.

The last question that I've got an east whether they're any structural visa and the date that would be expected to lose some more money you can make some more revenue.

I don't think that this is absolutely not that's in the data ragging increases we expect that each suggested EBITDA.

Mariz Espinelli: As Innodata revenue increases, we expect that its adjusted EBITDA will increase by an even higher percentage. This is because there is some operating leverage in our direct costs for things like production facilities and other fixed expenses and significant operating leverage in our general administrative operating costs. We saw clear evidence of this in both Q3 and in Q4. As in Q3, revenue grew sequentially by $2.5 million, and adjusted EBITDA grew sequentially by $1.6 million. Similarly, in Q4, revenue grew sequentially by $3.9 million, and adjusted EBITDA grew sequentially by $1.1 million.

It will increase it even higher per cent fees.

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Like in Q3, Verbing, you grew sequentially by 2.5 million and adjusted EBITDA sequentially by 1.6 million.

Similarly empty for letting you do sequentially by 3.9 million and adjusted EBITDA sequentially by 1.1 million. There will however be quite daily fluctuation on how much you had before so the EBIT line based on how the <unk> updating expenses, but he always.

Mariz Espinelli: There will, however, be quarterly fluctuations in how much revenue falls to the EBITDA line based on how we flex our operating expenses, particularly our sales and marketing efforts, based on market dynamics. Well, I hope I was able to address some of our investor queries. Again, thanks everyone, and I will now turn this over to John. John, we are now ready for questions. Thank you. At this time, we will be conducting a question and answer session. If you would like to ask a question, please press star 1 on your telephone keypad. The confirmation tone will indicate your line is in the question queue. You may press star 2 if you'd like to remove your question from the queue. For participants using speaker equipment, it may be necessary to pick up your handset before pressing the start button.

Sales and like getting F like based on my Kids dynamics.

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Thank you at this time, we will be conducting a question and answer session. If you would like to ask a question. Please press star one on your telephone keypad, a confirmation tone will indicate your line is in the question queue. You May press start to if you'd like to remove your question from the queue for participants using speaker equipment and may be necessary to pick up your handset before pressing.

<unk> one moment, please while we poll for questions. Once again, please press star one if you have a question or comment.

Operator: One moment, please, while we poll for questions. Again, please press star 1 if you have... The next question comes from Tim Clarkson. Hey Jack, how are you doing? Hey Tim, doing great. Good, good. Well, I thought the quarter was outstanding.

The first question comes from Tim Clarkson with Van Clemens. Please proceed.

Jack How're you doing.

It's I'm doing great.

Alright got wiped out the corner was outstanding. So just has a question I'm gonna have you answer it but you're gonna answer it.

Tim Clarkson: So just as a question, I'm going to have you answer it, but you'll answer it in a more sophisticated way than I'm going to say it. But I mean, when I originally learned about Innodata being involved in AI, Raul told me, and this is one that he told me when the stock was at a dollar, he said, listen, the reason Innodata is going to be successful is that they're the most accurate. And at IBM, the reason we had so much trouble on 80% of our deals was inaccuracy.

More sophisticated way, then I'm and I'm, saying that but I mean, when I originally learned about in it or be involved in AI raw will call me and this is what he told me when the stock was at a block he said listen.

Yeah, I was going to be successful is there the most accurate and an I b M. The reason we had so much trouble on 80 per cent of our deals was inaccuracy you know so far.

Tim Clarkson: And you know, so far, you've gotten a number of smaller contracts, and now you've gotten the big contracts, it's coming true. So to me, that's maybe a really simple insight for some people who are intimidated by all the complexity of AI. But why don't you explain in simplest terms how Innodata fits into AI? Sure. Well, in a number of different ways.

You've gotten a number of smaller contracts and all you've gotten the big contracts, it's it's coming true so to me.

That's maybe a real simple insight for some people who are in <unk>.

Imitated by all the complexity of of a I, but why don't you explain in the simplest terms you know how in a data fits into a I.

Sure well in in a number of different ways.

Jack Abelhoff: I think to myself, you know, I don't think your question is particularly unsophisticated. I think that exactly what you said is correct. The key to programming large language models is essentially the data engineering that goes into it, and the principle of garbage in, garbage out holds very much true. What I see that we're doing a great job at is creating very high-quality data sets that our customers are able to use and incorporate into the large language models to get the performance from the models that they're seeking, um, instruction data sets, you know, that are key to, you know, helping the And that's how they're competing.

I think two two.

And I don't think your questions, particularly unsophisticated I think fit exactly what you said is correct.

The key to programming large language models is essentially the data engineering that goes into it and the principal garbage in garbage out holds very much true.

What I see that we're doing a great job that is creating very high quality datasets.

That our customers are able to use an incorporated in the large language models to get the performance from the models that they're seeking.

Instruction datasets, you know that.

A key to helping the models understand prompts to accept instruction to converse to reason all of these things and that's how they're competing they're competing on the quality of the experience that their customers will have.

Jack Abelhoff: They're competing on the quality of the experience that their customers will have with the models that they're building. So to the extent that the data engineering that we provide to them is helping them achieve that, well, you know, that obviously is a very, very good thing. Now, on top of data accuracy and data engineering, the thing that we've been focused on for so long now, I think we create the appropriate customer experience that they're looking for. You know, they're figuring things out. They need a company that's highly dynamic and that's agile and that can, can, can, can stay with their engineering team. They can be responsive to the changing requirements that the engineering team has. And again, that's something that's firmly built into our culture.

The models if they're building.

To the extent that.

But the data engineering that we provide to them is helping them achieve that will you know that obviously is a very very good thing now on top of data accuracy and data engineering thing that we've been focused on for so long now.

I think we create fee appropriate customer experience that they're looking for.

They're figuring things out so you need a company that's highly dynamic and that's agile and that can can can.

Can can stay with their engineering team that can be responsive to the changing requirements of the engineering team has.

And again, that's something that's firmly built into our culture.

Jack Abelhoff: So we're very proud of the results that we're showing. We're very proud of the quality of the partnerships that we're achieving. I think, you know, well, we announced that for one of the large deployments this quarter, we signed a three-year ongoing contract with a potential value of $69 million. It's a huge achievement.

We're very proud of the results that were show and we're very proud of.

The quality of the partnerships that we're achieving.

I think I don't think we announced that for one of the large deployments. This quarter, we signed a three year ongoing contract with a hopeful value of $69 million. It's a huge achievement and what's that came with was.

Jack Abelhoff: And what that came with was a lot of wonderful things that the customers had to say about us, about the value of the data, exactly as you just said, and about the quality of the experience that they had with us. So we think we're, you know, we're doing good. We're very well poised for an exciting year next year, and we're very excited about it. Now looking at your projections, I mean, you said last time you expected some 30 million quarters. It looks like based on what you did in the fourth quarter and your growth rates. You know, we are approaching that sometime this year, right?

A lot of wonderful things that the customer had to say about us.

If that's the value of the data exactly like you just said about the quality of the experience that they have with us so.

So we think we're you know we're doing good we're very well poised for an exciting year next year and we're very excited about that.

Right now now looking at at your projections I mean, you said last time, you would expect some 30 million quarters. It looks like based on what you did in the in the fourth quarter and your growth rates.

You know approaching that sometime this year right.

Tim Clarkson: Well, I think we're going to stick with the guidance that we're providing. You know, our intention is to surprise and delight our investors. We think we have the opportunity to do that. Right. So the guidance that we've put out there is, you know, 20% growth, but with the intention of, of, of besting that. Sure. I think we have a very, very good chance of doing that.

Well I think we're gonna stick with the guidance that we're providing you know our our intention is to.

222 surprise and delight our investors, we think we have the opportunity to do that.

Right. So the guy that we've put out there is 20% growth, but with the intention of of of best thing that I'm sure. I think we have a very good chance of being able to do that.

Tim Clarkson: Right, right. Now, when I look at the P&L, I know you like to look at EBITDA; I like to look at net after-tax. It seems to me that somewhere as you approach, say, $35 million, at $30 million, you start to net 10 to 15 percent after-tax, and at $35 million, you start to approach, you know, more like 15 to 20 percent after-tax.

Right right now when I when I look at the P&L I know you would like to look at the other dog I like to look at net net after tax it seems to me that somewhere as you approach say 35 million or 30 million you start doing that 10% to 15% after tax and at 35 million you start to approach you know more like 15 to 20 per.

Sent after taxes is that about right.

We're not going to there are a lot of things that go into the model I think we're gonna resist the temptation of.

Tim Clarkson: Is that about right? You know, we're not going to, there are a lot of things that go into the model. I think that we're going to resist the temptation of kind of digging in and creating more of a model than we are. You know, the guidance is, you know, what we're saying. I think we intend to do better than that, and perhaps significantly. And I think, you know, the business is not that difficult to model. I'd encourage you to do it.

Kind of taking it and creating more of a model thin.

We are.

The guidance is.

What what we're saying I think we intend to do better than that.

And Roy have significantly and I think you know it.

Business is not that difficult to model I'm encourage you to do it I think we can create a lot of shareholder value of this year.

Right and I and obviously a sales go up historically within a day at all with the profitability of solace gone up on balance not every quarter, but typically it goes up much faster than the revenues.

Jack Abelhoff: I think we can create a lot of shareholder value this way. Right, and obviously, as sales go up, historically with Innodata, profitability has always gone up on balance, not every quarter, but typically it goes up much faster than revenue. That's correct.

That's correct and I think you see that operating leverage working.

Very strongly in both Q3 and Q4 in that operating leverage and the disproportion increases that we see in profitability to revenue growth.

Jack Abelhoff: And I think you see that operating leverage working very strongly in both Q3 and Q4. And that operating leverage and the disproportionate increases that we see in profitability to revenue growth will work for us, will continue to work for us, I believe, and will give us the ability to further invest in the company and stay aligned with our market and ahead of our competitors. And, you know, we think we're managing the company appropriately from that perspective. We're very happy, as we just said, to confirm that we don't plan on needing to raise equity.

Will work for US will continue to work for US I believe and will give us the ability to further invested in.

In the company and stay aligned with our market in the head of our competitors and.

We think we're managing the company appropriately from that perspective, we're very happy as we just to confirm that we don't plan on leaving to raise equity.

We think that that's <unk>.

Very strong statement for a company that has been able to.

Jack Abelhoff: We think that that is, you know, a very strong statement for a company that has been able to keep pace with, you know, others of our competitors who are more significantly funded than we are and to compete aggressively with them and win deals against them. So, you know, we think we're managing the opportunity appropriately, and we think there are a lot of good things ahead for us. Right. A little softer question. Can you explain, you know, not the big guys, but say a smaller application. You mentioned a drugstore where they might want to use AI as their customer service.

Keep pace with.

Others of our competitors, who or more significantly funded than we are.

And to compete aggressively with them and when deals against so we think we're we're managing the opportunity appropriately and we think there is a lot of a lot of good things ahead for us.

A little softer question can you explain you know not not the big guys, but say a smaller application you mentioned, a drugstore, where they might want to use a I as as our customer service kind of explain what that would look like or or a retail shop, where they're using a I <unk>.

Tim Clarkson: Kind of explain what that would look like or retail shop where they're using AI rather than necessarily people to get business done. Sure, well, you know, I'll give you a fresh example, not even from the work that we're doing today, but from the work that I'm hopeful that we'll be doing at some point in the near future where we're in conversations with a, kind of a home furnishings manufacturer who wants to create the ability for someone to upload pictures, to their website and to utilizing those pictures to discover which of their furnishing products would fit best within that environment and maybe even display what that might look like. So I think as you go from. Enterprise to enterprise, you know, firstly, I think it's it's almost inconceivable that there will be enterprises who won't be affected and likely benefit, from these technologies if they seize them correctly, and the fact that, you know, as we do the work that we're doing with the Foundation Model Builders. We're also continuing to plant seeds in enterprise and to work soup to nuts, with enterprises to figure out how do they take advantage of these technologies and seize these opportunities is, I think, planting very strong seeds for the future. Right. Okay, I'm done. Thanks. The next question comes from Dana Busca with SouthO. Hi, Jack. Hey, David.

Other than necessarily people to I'll get business done.

Sure well I'll give you a fresh example, not even from the work that we're doing today books from the work that I'm hopeful that we'll be doing at some point in the near future were really conversations with a.

Kind of a home furnishings manufacturer, who wants to create the ability for.

Someone to upload pictures to their website and to utilizing those pictures to discover which of their furnishing products would fit best within that environment, and maybe even display what that might look like.

So I think as you go from.

Enterprise two enterprise Firstly I think it's it's almost inconceivable that there will be enterprises, who won't be affected and likely benefit.

From these technologies of the system correctly and.

And the fact that you know as we do the work that we're doing good.

With the foundation model builders, we're also continuing to plant seeds and enterprise into work soup to nuts.

We've enterprises to figure out how did they take advantage of these technologies and cease these opportunities.

Is I think planning very strong seats for the future.

Right, Okay I've done thanks.

The next question comes from Dana Bhaskar with South though please proceed.

[noise] hijack.

Dana Busca: Congratulations on an excellent quarter. Well, thank you so much. We're very happy with the quarter. We're happy with how we're kicking off 2024. Oh, wonderful. My first question I have is about your GoldenGate platform. It is my understanding that that's built on the transformer architecture, and is that like the same architecture that OpenAI uses?

Hey, Dana.

Congratulations on an excellent Carter.

Well. Thank you so much we're very happy.

Quarter are happy.

You know, how we're kicking off 2024.

Wonderful.

My My first question I have is that I I just want to ask the question about your Golden Gate platform.

It is my understanding that that's built on the transformer architecture.

And isn't that like the same architecture that open a I use is <unk> and.

Jack Abelhoff: And I was just wondering what that means for your offerings? Sure, so I believe that it is the same architecture and, And when we see that it is what we mean to www.kinstlinger.com, solid future-proofed engineering decisions within our Engineering Department. And I think that's important, because it's not trivial to make those decisions, and it's not obvious when you're making them whether you're making the right one. Now, you know, that having been said, we are not, by any measure, saying that we can use the Golden Gate as a substitute for CHAT GPT. That's far from the case,

And I was just wondering what does that mean for your offerings.

Sure. So I believe that it is the same architecture and.

And when we see that is what we mean to use that as a proof 0.4 is that we're making good <unk>.

Solid future proofed engineering decisions within.

Our engineering Department.

And I think that's important because it's not trivial to make those decisions and it's not obvious when you're making them, whether you're making the right ones.

No.

That having been said we are not by any measure, saying that we can use the golden gate as a substitute for CECI P. T. That's far from the case Golden Gate is 50 million parameters, we believe CECI P T as 1.7 billion parameter.

Jack Abelhoff: Golden Gate is 50 million parameters. We believe CHAT GPT is 1.7 billion parameters. You know, Golden Gate does very specific things that are good for us and good for our customers in our business. We use it in many, many of our deployments. But you can't ask it to write a poem about butterflies and iambic pentameter.

States Golden Gate does very specific things that are good for us and good for our customers and our business we use it many many of our deployments.

Yeah, but you can't ask it to write a poem about butterflies in iambic pentameter. It just doesn't.

Jack Abelhoff: It just does, www.innodata.org. The fact is, though, that we picked the right technology, and we're using it very effectively in much of what we're doing. It was very, very useful in the work that we were doing for big tech companies in classic AI. It has less utility in large language models but continues to have lots of utility in our business. Okay, wonderful. I'm working on the kind of fast moving marketplace and fine tuning and reinforcement learning. Do you have any estimates about how large that market is right now? You know, I think there are a lot of different estimates.

Work for that.

The fact is though that we pick the right technology, we're using it very effectively and much of what we're doing.

It was very very useful in the work that we were doing for big Tech companies and classic a I.

It has less utility in large language models.

Continues to have lots of utility in our business.

Okay wonderful.

With the kind of fast moving market place in my fine tuning and reinforcement learning.

<unk> do you have any estimates about how large that market is right now.

So you know I think there are a lot of different estimates the one that we've shared in the past doesn't have the data in front of me, but the the one that we shared the past was Bloomberg estimate looking at.

Jack Abelhoff: The one that we've shared in the past, I don't have the data in front of me, but the one that we shared in the past was a Bloomberg estimate looking at, you know, AI and large language modeling related services and showing that there would be a significant expansion in that market. I'd probably point you to that and be, you know, happy to send you a reference for that after the call. Okay. Okay. Great! That's excellent.

Hey are in large labs language model related surfaces, and showing that there will be a significant expansion in that market.

Probably point, you to that and be happy to send you a reference for that after the call.

Okay, Okay, great that's excellent <unk>.

Dana Busca: And at the last couple of conferences, you talked about your white label agreement, and I was just wondering how that is going? Are you seeing any inroads with that? Yeah, we're seeing inroads. We still think it's early days.

And and the last couple of cough cause he's talked about your white label agreement and I was just wondering how how is that going have you seen any in relative with that.

Yeah, we're seeing in roads still tickets early days again, it's early days for enterprise applications.

Jack Abelhoff: Again, it's early days for, you know, enterprise applications as a whole. Um, We had a very good quarter with that customer in Q4. I think we're going to see pickup from the white-label partnership beginning in Q1 and probably through the year.

Applications, you know as a whole.

We had a very good quarter with that customer.

In Q4.

I think we're gonna see pick up from the white labeled partnership beginning in Q1 and probably through the year.

Jack Abelhoff: But again, I view that very much as a seed that we've planted for the enterprise side of the business. Right now, the growth that you're seeing is primarily in the work that we do. The data engineering work that we do for the internal builds that the hyperscalers and large tech companies are working on. Okay.

But you know again I view that very much as a seed for the entered that we've planted for the enterprise side of the business right now the growth that you're seeing is primarily on the work that we do.

The data engineering work that we're doing for the internal builds that the hyperscalers in large companies are.

Are working on.

Okay, and what strategies are you appointed to differentiate yourselves from your competitors.

Jack Abelhoff: And what strategies are you employing to differentiate yourselves from your competitors? So I think, you know, it depends on the line of business. If you think about the services side of the business, which is the bulk of the business, it's 80% of the business.

So I think you know it it's.

It depends on the line of business. If you think about the surface the side of the business, which is the bulk of the business, it's 80% of the business.

Jack Abelhoff: What we need to do is no different than any other services company would need to do. We have to do a very good job at what we're hired to do. Just like the question Tim asked. He said, Well, you know, is data quality really important? And I think the answer to that is, as I said, it clearly is critical.

What we need to do is no different than any other services company would need to do we have to do a very good job, but what were hired to do.

Just like the question Tim asks he said well you know.

<unk> is the <unk>.

Data quality.

Really important and I think the answer to that is as I said. It clearly is critical that's what we're being hired to do.

Jack Abelhoff: It's what we're being hired to do. You know, beyond that, you care about the level of service that you're obtaining; you care about the quality that the vendors are bringing to the relationship. You care about how tightly aligned they are with your engineering team and whether, you know, when they zig, you can zag and whether you can follow, follow their lead and be responsive to their changing requirements.

Beyond that you care about the level of service that you're obtaining you care about the <unk>.

Qualities that the.

<unk>.

The vendors, bringing to the relationship you're carrying about how tightly aligned they are with your engineering team and whether you know when the <unk> Zag and whether you can follow followed their lead and be responsive to their changing requirements.

Jack Abelhoff: We're bringing that to the table. Okay, excellent. And do you have any new products or services that you're excited to be introducing this year? Yeah, so I think there's a lot that's going on, you know, when you look at the field as a whole, what you see and what we're starting to see is the spread of activities around, you know, languages, around domains, around what we call text-to-X, you know, the different modalities that large language And again, I focus on that because it's within the growth area of our services that is most important. So we're doing a lot of work on those areas. We're also doing a lot of work in terms of trust and safety and aligning our capabilities to their emerging requirements in terms of helping ensure that the models perform as expected. That's going to be an important area.

We're bringing it back to the table.

Mmk excellent and do you have any new products or services that you're excited to be introduced in this year.

Yeah. So I think there's a lot that's going on you know when you look at the.

When you look at the field as a whole what you see and what we're starting to see if.

Is the spread of activities around language surrender means around what we call a text to X. The different modalities that large language levels are going to be required to support.

And again I focused on that because it's within.

The growth area of our surfaces that is most important so we're doing a lot of work on those areas. We're also doing a lot of work in terms of trust and safety and lighting our capabilities to very emerging requirements in terms of helping ensure that the models perform as expected.

That's going to be an important area.

Jack Abelhoff: In other areas of the business, we're releasing new product capabilities. We've got some things coming out in medical data extraction that we're excited about. We've got an AI roadmap that is very compelling and, you know, being received now well kind of in beta by customers in the agility segment, so we're excited about that as well. Do you have any plans to do images with Agility? I'm sorry, doing images? Yes.

In other areas of the business, we're releasing new product capabilities, we've got some things coming out and medical data extraction that we're excited about we've got.

AI roadmap that is.

Very compelling and you're being received now well kind of invader by customers and the agility.

Segments. So we're excited about that as well.

Do you have any plans to doing images that with agility.

I'm sorry doing images.

Dana Busca: So I think that the primary use case of agility is a media intelligence platform, and it's a workflow for PR professionals that require the ability to both target audiences with messages to craft those messages to find out, you know, who to target best to send those messages to, and then to analyze, pick up, and monitor news and social media globally. So there's not really a huge requirement for images within that product other than what we've already integrated. So, for example, we've already integrated AI that can be used to monitor news and imagery within the news. So if your logo, for example, is contained in a piece of news, we can inform our customers that that has been observed. OK, great. That does it for me.

Images yeah.

So I think that the.

It either.

Primary use case of agility <unk> intelligence platform and it's a.

Into wind.

Workflow four P. R professionals that require the ability to both target.

Audiences with messages to to craft those messages to find out who to target best to send those messages too.

And then to analyze pick up and to monitor.

News and social media globally, so there's not really a huge requirement for images within that product other than what we've already integrated. So for example, we've already integrated AI that can be used to monitor news and imagery within the news. So if your logo for.

Example is contained in the piece of news we can we can inform our customers that said that has been observed.

Okay great.

That does it for me thanks for answering my questions.

Dana Busca: Thanks for answering my questions. Thank you. Once again, if you have a question or a comment, please indicate so by pressing star 1. Up next is Bill Thompson with Karo Capital. Hey, good afternoon.

Thank you.

Once again, if you have a question or comment please indicate so by pressing star one up next is bill Thompson with Cairo capital. Please proceed.

Good afternoon.

Bill Thompson: Hi Bill, good afternoon. Congratulations on the quarter. I was pleasantly surprised to see that the company made a profit, based on its recent performance. That's definitely a nice change.

Hi, vulgar afternoon.

Congrats on the corner I was I was pleasantly surprised to see that the company made a profit you know based on the recent performance that's definitely a nice change.

Jack Abelhoff: I had a question about the agility business. You have stated multiple times that the agility business is actually profitable as it stands now. Is that on a gap basis, or is that by adjusted EBIT? It is both GAP and adjusted EBITDA, but we do use adjusted EBITDA as a core metric, you know, because we think that it is. It's useful. When we're looking at adjusted EBITDA, we're carving out, as you may be aware, DNA, stock option expense, you know, obviously income tax, and then, you know, one-time severance costs that are not recurring, but it was also profitable, and I got this. Okay, and you're sure about that? Yes, I'm looking. I'm looking through the announcement, and it's unclear. It's not usually broken out.

I had a question about the agility business.

So you said multiple times that the agility businesses actually profitable.

As it stands now is that on a gap basis or is that by adjusted EBITDA.

So we.

It is both gap N adjusted EBITDA, but we do use adjusted EBITDA as a cord metric close where you think that is it.

Useful.

When you were looking at adjusted EBITDA, We're carving out as you may be aware, we're carving a DNA.

Stock options expense you know, obviously income tax and then one time severance costs that are not not recurring.

But it was also profitable unto got basis.

Okay, and you're sure about that.

Yes, I'm looking I'm looking through the announcement and it's unclear.

It's not usually broken out.

Jack Abelhoff: I have another question. We'd be happy to, you know, separately take you through that and answer any detailed questions you have. Okay, that would be excellent.

I I have another question so we'd be happy do separately take you through that and answer any detailed questions you have.

Okay that'd be excellent I haven't <unk>, you had a very experienced C. F O two years ago.

Bill Thompson: I have another question. So you had a very experienced CFO for two years, and the person resigned, I believe it was two days before the report was signed and submitted to the SEC. So it was pretty abrupt.

The person resign I believe it was two days before.

Report was signed and submit it.

S a C.

It was pretty abrupt and then the company put in place an interim CFO.

Bill Thompson: And then the company put in place an interim CFO, and it's been two years. The company claimed that they were, well, you at the time, you claimed that you were in the process of looking for a full-time CFO. However, it's been two years, and there's still an interim CFO. Can you give us an update on that process of looking for a certain sample?

And it's been two years the company claimed that they were you at the time of your claim that you were in the process of looking for full time CFO Uhm.

However, it's been two years and they're still an interim CFO.

Could you give us an update on that process of looking for sure.

Jack Abelhoff: So in, I think it was March of 2021, we hired a SVP of finance and corporate development, and his function and his mandate was to put in place a stronger strategic finance function than we had at the time. We saw that that was an important need that we had. And, you know, what that function does is it looks at

So.

So in I think it was March of 2021, we hired a S V P of finance and corporate development.

And his function in his mandate was to put in place a stronger strategic finance function than we had at the time, we saw that that was an important need that we had.

And you know what that function does it looks it.

Jack Abelhoff: It looks like how we're managing cash. The return that we're getting on investments that we're making, it looks at and takes ownership of our budgeting and all of those functions. So it's kind of, you know, strategic day forward, looking forward, providing leadership around how we're managing the business and the investments that we're making. We already had very strong talent in terms of the controllership function. What we found, you know, with hiring this person and the talent that we have in place, is that we've got strong talent kind of, you know, end to end right now in the finance function. I think arguably the piece that we may be lacking is the piece that we need to think through more carefully.

How we are managing cash it looks it.

The return that we're getting on investments that we're making it looks it and it takes ownership of our budgeting.

And all of those functions. So it's kind of strategic day forward looking forward.

Providing leadership around how we're we're managing the business and the investments that we're making.

We already had very strong talent in terms of the controllers should function.

What we found with hiring this person and the channels that we have in place is that we've got strong talent kind of into and right now in the in the finance function.

I think arguably the peace that we may be lacking in the peace that we need to think through more carefully.

Jack Abelhoff: As it becomes more important is the investor relations component, the public company component; are we spending enough time, you know, doing outreach with investors? I hate to interrupt, but I know you like to editorialize a lot, but are you saying that you currently don't need a full-time CFO and that the interim is going to continue? What I'm saying is that as we think about the need for a CFO, we're doing a lot of thinking about the investor relations function and, you know, the role of someone who would be working with our analysts who may be thinking about covering our company and things like that from a perspective of capabilities for what we need today. I think we're very, very well covered, and we've got very strong talent in place.

As it becomes more important is the investor relations component the public company component are we.

Spending enough time doing out nation that I hate turning up I ended up but I know you'd like to editorialize on that but are you, saying that you currently don't need a fulltime CFO and at the Android is going to continue.

What I'm, saying is that as we think about the need for CFO, we're doing a lot of thinking about.

The Investor relations function and.

The role of someone who would be working with our.

Analysts who may be.

Thinking about covering our company and things like that from a perspective of capabilities.

What we need today I think were very very well covered and we've got very strong talent in place.

Bill Thompson: Okay, and then one last thing is, I'm looking at the numbers from the press release, and it looks like agility had a $1.3 million gap loss. Can you verify that, either the CFO or yourself, Jack? So we, I don't have the numbers in front of me right now, but we had a gap profit. And again, I'm very happy offline to put you in touch with any kind of a big deal. You guys just finished the quarter. You should know the gap profitability of your business segment. Do you guys have a straight answer for that?

Okay, and then one last.

I'm looking at the numbers from the password resent it looks like the Jillian you had a 1.3 million dollar capital loss.

Can you verify that is the <unk> or yourself Jack.

So we don't have the numbers in front of me right now, but we had a gap Crawford and again.

Very happy offline to put you in touch with any kind of a big wheel you guys. Just finished the corner you should know the gap profitability of your business segments.

She doesn't have a straight answer for that.

Bill Thompson: So, well, I think that I'm not sure exactly what you're trying to get me to say. I told you that I just want to know how I'm investing in the company. I would like to know how much money the company is making. It's pretty straightforward.

So well I think that I'm not sure exactly what you're trying to get me to say I told you that I just wanted to know how often I've invested in the company I would like to know how much money. The company's my account, it's pretty straightforward.

Jack Abelhoff: So we had $440,000 of gap profit in agility in the quarter because I'm seeing a net loss of 1.35 for the year. Very happy to have a call with you to drill down to that and look at what you're looking at and at that difference from what we're reporting. I don't know how I can help you beyond that. Alright, I appreciate it.

So we had $440000 of profit and agility in the quarter.

Cause I've seen a net loss of 1.350.

Again with a ear very helpful very happy to have a call with you to drill down to that and look at what you're looking at it.

That differs from what we're reporting.

How I can help you be on them.

Alright I appreciate it.

Jack Abelhoff: We have reached the end of the question and answer session. I will now turn the call over to Jack for his closing remarks. In 2023, you know, the world witnessed a seismic shift with the arrival of OpenAI's chat GPT. It was a phenomenal event.

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

Thank you.

In 2023, you know what the world witnessed a seismic shift with the arrival of open a is judged P T.

Steal the spotlight it wasn't just another software release it was a.

Jack Abelhoff: It captivated the world with its abilities to do what seemed like superhuman feats, and this sparked a wave of development with companies vying to push the boundaries of language generation and its applications. We saw that there were tech giants locked in a heated race to dominate the realm of generative AI models, and this arms race resulted in billions of dollars of ongoing investment being made by these companies with ripple effects potentially reshaping every industry we know. It's essential to emphasize, and I think a couple of these questions were useful in that regard, that in the realm of training large language models, the age-old adage of "garbage in, garbage out" holds particularly true.

<unk> captivated the world with disabilities to do what seemed like Super human feats and this sparked away from development with companies wanting to push the boundaries of language generation and its applications.

We saw that there were tech giants locked in a heated race to dominate the realm of January <unk> models, and disarm race resulted in billions of dollars of ongoing investment that.

Being made by these companies would ripple effects potentially reshaping every industry we know.

It's essential to underscore and I took a couple of these questions were useful in that regard that in the realm of training.

Large language models, the eight age old adage garbage in garbage out holds particularly true.

Jack Abelhoff: This is where our distinct advantage comes to light, as we've been consistently delivering high-quality data at scale for 30 years. One of our competitive advantages lies in providing unparalleled data quality, which serves as the foundation for successful AI implementations. Moreover, our success is bolstered by the entrepreneurial and collaborative culture that we've cultivated over the decades, engaging with large corporations across diverse industries. This empowering culture has enabled us to compete with other businesses at a remarkably high success rate, driving our continued growth and our achievements. We saw a business pick up momentum through the year as we began to seize the generative AI opportunity, and we met or exceeded expectations on all fronts, revenue growth, adjusted EBITDA growth, and key customer acquisitions. In Q4, the same thing.

This is where our distinct advantage comes to play as we've been consistently delivering high quality data, it's scaled for 30 years.

One of our competitive advantages license, providing unparalleled data quality, which serves as the foundation for successful implementations.

Moreover, our success is bolstered by the entrepreneurial and collaborative culture that cultivated over the decades engaging with large corporations across diverse industries.

This empowering cultures enabled us to compete with other businesses is remarkably as success rate driving our continued growth in our achievements.

We saw a business to pick up momentum through the years, we began to seize the journey today I opportunity and we met or exceeded expectations on all fronts revenue growth adjusted EBITDA growth and key customer acquisition.

In queue for same thing, we beat both top and bottom line guidance and we entered three year 23 million per year jail with a <unk>.

Jack Abelhoff: We beat both top and bottom line guidance, and we entered a three-year, $23 million per year deal with a key big tech customer for the program we kicked off mid last year, a testament clearly to how highly they valued our collaboration. We're off to an exciting start to 2024, you know. As you know, we're now engaged with five of the magic seven for generative AI development, and we're seeing the benefits of this engagement in our results. In 2024, we will be working to drive expansion in all these accounts and to land others. We're guiding to 20% growth in 2024, but our ambition is to exceed that. My team and I are energized by what we've accomplished in 2023, and we're excited about what we will accomplish in 2024. So thank you all for joining the call today. We look forward to our next call. This concludes today's conference, and you may disconnect your lines at this time. Thank you for your participation. www.kinstlinger.com

He big Tech customer for the program, we kicked off mid last year, it's estimate clearly to have highly valued our collaboration.

We're off to an exciting start to 2024.

You know now we've we're now engaged with five of the Mag seven for generative AI development, we're seeing the benefits of disengagement and our results.

In 2024, we will be working to drive expansion and all of these accounts into land others.

Regarding to a 20% growth in 2024, but our ambitions to exceed that.

My team and are energized by what we've accomplished in 2023 and we're excited about what we will accomplish in 2024. So thank you all for joining a call today will look forward to our next call.

This concludes today's conference and you may disconnect your lines at this time.

Thank you for your participation.