Earnings Transcript for INOD - Q1 Fiscal Year 2023

Operator: Greetings. Welcome to Innodata's First Quarter 2023 Earnings Call. [Operator Instructions]. I will now turn the conference over to your host, Amy Agress. You may begin.

Amy Agress: Thank you, John. Good afternoon, everyone. Thank you for joining us today. Our speakers today are Jack Abuhoff, CEO of Innodata; and Marissa Espineli, Interim CFO. We'll hear from Jack first, who will provide perspective about the business, and then Marissa will follow with a review of our results for the first quarter. We'll 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 21E of the Securities Exchange Act of 1934 as amended, and Section 27A of the Securities Act of 1933 as amended. Forward-looking include, without limitation, any statements 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 and including, without limitation, the expected or potential effects of the novel coronavirus, COVID-19 pandemic and the responses of government of the general global population, our customers and the company there to impacts from the rapidly evolving conflict between Russia and the Ukraine; investments in large language models that contracts may be terminated by customers; projected or committed volumes of work may not materialize; pipeline opportunities and customer discussions, which may not materialize into work or expected volumes of work; acceptance of our new capabilities, continuing 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 market, particularly new and emerging markets that our services and solutions support; continuing Digital Data Solutions segment revenue concentration in a limited number of customers, potential inability to replace projects that are completed, canceled or reduced; our dependency on content providers in our Agility segment; a continued downturn in or 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 requirements for our services and solutions; difficulty in integrating and driving synergies from acquisitions, joint ventures and strategic investments; potential undiscovered liabilities of companies and businesses that we may acquire potential impairment of the carrying value of goodwill and other acquired intangible assets of companies and businesses that we acquire; changes in our business or growth strategy; the emergence of new or growth in existing competitors, our use of and reliance on information technology systems including potential security regions, cyber attacks, privacy breaches or data breaches that result in the unauthorized disclosure of consumer, customer, employee or company information or 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.

Jack Abuhoff: Good afternoon, everybody. Thank you for joining our call. As you probably saw in our announcement earlier today, we have quite a lot of exciting news to share with you. Over the last couple of weeks, we received verbal confirmation from 2 of the largest 5 global technology companies that we have been selected to provide data engineering for their innovation programs in generative AI, the technology behind ChatGPT. One of these companies is an existing customer and the other one will be a new customer. In addition, a third company, also a new customer and another of the largest 5 global technology companies, has indicated that they are likely to choose us and we have just reached agreement with them on terms of a master services agreement. We believe these accomplishments are potentially transformative for Innodata. For these companies, we expect to be performing a range of data engineering work required to build cutting-edge generative AI. We expect this potentially to include creating training data sets that are used to train the models, providing instruction data sets that teach the models to follow instructions, providing reinforcement learning, a process by which we align models with human values and complex use cases and providing red teaming and model performance evaluation. This involves potentially working in multiple languages and across several data modalities. I will be focusing today's call on first

Marissa Espineli: Thank you, Jack. Good afternoon, everyone. Allow me to provide a recap of our Q1 results. Revenue for the quarter ended March 31, 2023 was $18.8 million compared to revenue of $21.2 million in the same period last year. And as Jack mentioned, the comparative period included $4.4 million in revenue from large social media company that underwent a significant management change in second half of last year, as a result, it dramatically pulled back spending across the board. There was no revenue from this company in the quarter ended March 31, 2023. Net loss for the quarter ended March 31, 2023 was $2.1 million or $0.08 per basic and diluted share compared to net loss of $2.8 million or $0.10 per basic and diluted share in the same period last year. Our adjusted EBITDA was $0.8 million in the first quarter of 2023 compared to adjusted EBITDA loss of $1 million in the same period last year. Our cash and cash equivalents, including short-term investments, were $10.8 million at March 31, 2023, and $10.3 million as of December 31, 2022. Again, thanks, everyone. John, we are now ready to take questions.

Operator: [Operator Instructions]. And the first question comes from Tim Clarkson with Van Clemens.

Tim Clarkson: Jack, exciting news. This is kind of a basic question, but my customers always ask it, so I'll ask it for them. How many other companies could potentially do the kind of stuff you're doing in AI?

Jack Abuhoff: It's a good question, Tim. I mean, I don't have a real account on that. There are several companies that we do run up against that are talked about in the marketplace. I can tell you that on 1 of the 3 customers that who's likely winning we're announcing today, we were told that we were competing against 17 companies. And that competition has been going on for several months. It was started with 17, it got narrowed to 4. And then as I said, it's looking very good in terms of being able to call that a win and getting that signed. So I guess there's at least 17 that are entering the fray. I expect that there will be many more. I think that there's a very exciting opportunity, which as I presented a little bit of today. And I think it's fortunate the residues somewhat of luck and some good decisions in planning that we're in the position that we are. So it's very exciting, and I believe transformative potentially for the company.

Tim Clarkson: Okay. So kind of a follow-on question. What are the factors you think that are allowing you to get these contracts in competitive situations?

Jack Abuhoff: I think what it all comes down to is skills, technology, capabilities and culture. We've got a culture of being very agile, very able to move quickly and to respond to customer demand, customer centricity, understanding what people want, listening really, really super carefully to their needs and kind of embedding us as parts of that team. And then it comes to some of the things that I mentioned on the call today. We're fortunate to have the skills ready to repurpose that are exactly what are required in order to build these technologies scalable domain expertise, the ability to create and the proven ability to create high-quality, very consistent data sets and complex subjects, 40 languages, the technical acumen at having built the recipes and the technologies to do AI model training and fine-tuning and having chosen the right architectures over the years, I think all of these are playing a great part in the track record that we're now establishing. Look, I'm like thrilled, 3 out of 3, looking very strongly. And I think we're -- I'd like to think we're just getting started.

Tim Clarkson: Right. Supposedly, when Microsoft did their ChatGPT supposedly a lot of the annotation was done in Kenya for $3 an hour. I mean is there a difference in the kind of annotation you guys do versus that kind of annotation?

Jack Abuhoff: Yes, there is. There was a great deal of difference. Some of the early models that have been built kind of go very broad, but very narrow. There's not a great deal of annotation that's required. Much of what we do is the complex stuff. It's going deep into subject-matter domains. It's going deep into use cases. I think it's the next phase of what will be required, both among the large tech companies as well as other companies that are looking to own that foundation layer as well as large businesses. So we're saying, look, we've got tremendous amount of data and information that's proprietary. We're not looking to serve that data up to the foundation models via their APIs, we want to control this. And I think that will, for them, probably make a ton of sense in light of the developments that are taking place with kind of the commoditization of the technology itself and the availability of it. All of that puts us in a great position to be able to be helpful and to be able to create great ROI on these capabilities that will probably become table stakes.

Tim Clarkson: Right. Right. Now at what level of revenues do you think you're going to have to add employees, would it be a $25 million a quarter or $30 million a quarter or $35 million a quarter. At what level would you think you would have to add employees?

Jack Abuhoff: So I think it's going to depend a lot on exactly what we're going to end up being doing. There are people that are in our cost of goods, and we typically don't keep those people around in terms of services work that we do. So there are people that will be added. But I think the important thing is that that's kind of in COGS. I think from a perspective of infrastructure of core operations, we've got what we need to begin executing on these contracts. There isn't something that needs to be built. There isn't something that we need to go acquire in order to execute. So we're ready to go.

Tim Clarkson: Sure. Now I saw that you got a line of credit. What -- how does that fit into the business situation?

Jack Abuhoff: Yes. So we thought that it was the right thing to do to have that in place. We were anticipating that we might win one of these large opportunities. And that it would be useful in terms of helping us manage working capital. That said, it looks like we've got potentially a great chance of having 1 off 3. And then there's more behind that, hopefully coming. So I think it's from a corporate housekeeping perspective from a corporate governance perspective, it's the right thing to have in place. And I'm very happy to say that we have it in place. And we've had great -- we have a great relationship with Wells Fargo that has started as a result of that. Very happy to be working with them.

Tim Clarkson: Sure. Any color on Synodex and Agility?

Jack Abuhoff: Yes, sure. They're doing well. From an Agility perspective, we had a 4% sequential growth rate in the quarter that annualized to like a 17% growth rate. We did a lot of cost cutting there, but what we were able to do was to really hone in on and focus our resources and the best performing 50% of the sales force. They're doing wonderfully right now. We're very happy with that. For example, we just bagged a $200,000 per year subscription deal with a large automotive company in Agility. We built the PR CoPilot, the generative AI model that we launched within the platform in January. It was the first mover within that industry. We've got great strong customer reception, a super cool road map for successive releases around that this year. And we're using that to like build a strong stand-alone asset as well as a playground to be able to show other customers, well, here's what you can do. Here's the way you can integrate these technologies and think about creating value from them in a safe and trusting way today.

Tim Clarkson: Right. What about Synodex?

Jack Abuhoff: Yes, sure. So Synodex, we had like -- I think it was 8% sequential growth, which would translate into a 36% annualized growth rate. A lot of the effort that we're doing this year is on expanding addressable market with new product models and new development. We're working really closely. A couple of very large life insurance companies as charter customers testing new capabilities and disability claims processing, long-term care claims processing, personal injury even and increasingly, AI is becoming an integrated feature of that capability as well.

Operator: [Operator Instructions]. The next question is from Dana Buska with Feltl.

Dana Buska: What you were saying and you wrote in your press release, just sounds amazing. I have a question around the large language models with them being so new. It sounds to me like you're getting the road map as you go. And I was -- which I think is a very, very exciting place to be. And I was just wondering what type of advantages does that give you that you are over your competitors that you're working with these large companies being, should we say, the first mover doing this type of stuff?

Jack Abuhoff: Yes. I think it gives us potentially a tremendous advantage. And again, we see opportunities kind of on 2 sides of the fence here. One is helping companies build these models and the second is helping them deploy and utilize the technology. So when the work that we're doing with the large tech companies, we're getting exposed to all sorts of new technologies. We're creating -- we're seeing things before they -- well before they come out potentially. And that gives us the ability to help companies kind of think through how they would deploy things. In addition, as we go about these tasks, we're building new capabilities. We're going to be building new technologies and new systems and through that process, identifying weaknesses in existing technologies and trying to innovate around that. So I think with everything that we do, we become stronger and we become better. My prediction that is behind these large tech companies, there's another 40 either well-funded start-ups or large tech companies who are going to be closely following. We're having conversations with several of them. And then beyond that, I think companies that are large companies with significant proprietary information assets will over time, have the ability and be able to make a use case for building LLM themselves. And again, I think we'll be very well positioned to partner with them to do that. So that we're winning these are critical. It will accelerate our innovation. It will accelerate our capabilities and make us more valuable progressively as we go from there.

Dana Buska: Excellent. That also sounds wonderful and amazing I recently saw a paper that was out of Stanford talking about being able to use large language models to do reinforced learning. Is that something that you think would potentially be some type of issue for you? Or do you do not consider that to be a threat to your business?

Jack Abuhoff: Yes. I missed the term that we're using Stanford study that shows that confused for what exactly?

Dana Buska: Stanford University that large language models could be used to do reinforced learning?

Jack Abuhoff: Reinforcement learning?

Dana Buska: Yes, reinforcement learning, sorry.

Jack Abuhoff: Yes. So reinforcement learning, sometimes called RLHF is basically used as part of one of the processes to build the model and to fine-tune the models. You're basically comparing the output of language model to human-generated pairs of questions and answers, and then you're modifying the internal variables to favor the responses that are similar to the human responses. So that's inherent process in the model fine-tuning itself.

Dana Buska: Okay. And then when we start -- when you start looking at building like your prompt engineering practice, do you have those people on staff right now? Or is that some place where you're going to have to start hiring people. How do you look at creating these new -- almost new jobs that you're going to need these new positions that you're going to need to fulfill your ambitions?

Jack Abuhoff: Yes, it's a great question. We're finding that -- these skills do not exist in surplus in the world. I was showing several weeks ago, a job ad for hiring a prompt engineer for $250,000 a year, which I don't know if that was real or not. But it made its way around the Internet. We're taking people that have been with us for a long time within our engineering group, they're figuring out prompt engineering. There's no real book written about prompt engineering or prop management or prop chaining, but we're building techniques. And one of the great things about our company is we've got so many real-world applications of these technologies. So it's not academic, it's not theoretical. We're like figuring out how do you deploy this safely and in a trustworthy way into real-world production scenarios. And from that, there's a tremendous amount of learning that we're capturing and can repurpose for our customers' continued benefit.

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

Jack Abuhoff: Operator, thank you. So yes, I'll quickly recap. Today, we're announcing that we have received verbal wins from 2 of the top 5 global tech companies and that we have a strong indication of a win from a third of these 3 companies, 2 our new customers. These are all companies that are widely expected to forge the path forward in generative AI development over the next several years. Last quarter, we cautioned you that these were just pipeline, and the pipeline often does not close this quarter. We're proud to say that 2 are now verbally confirmed wins and that we got a strong indication from the third that it also is likely a win. We hope to have each of these papers in the next few weeks. We believe that these new deals, perhaps individually, but certainly in the aggregate, present a potential transformative opportunity for our company. As you know, we have a solid track record of land and expand with large tech companies. And now with the additional tailwind of generative AI, we think we are extraordinarily well positioned. We believe the revenue growth opportunity with these companies is significant in the near, medium and long-term perspectives. We're also excited about the endorsement. We believe these new wins and accomplishments represent for us. We believe virtually every company out there will need to become an AI company over the next several years, and we believe that we will be well positioned to help them do just that. I also want to say that we plan on stepping up our Investor Relations activities in the second half of the year. We plan to be presenting at several investor conferences, and we will announce these once plans are firmed up. So again, thank you, everybody, for joining us today. We'll be looking forward to our next call with you.

Operator: This concludes today's conference, and you may disconnect your lines at this time. Thank you for your participation.