Good day, everyone, and welcome to the Innodata Q3 2024 Earnings Conference Call. At this time, all participants are in a listen-only mode. Later, you will have the opportunity to ask questions during the question-and-answer session. You may register to ask questions at any time by pressing the star and one on your telephone keypad. You may withdraw your question by pressing star two. Please note this call may be recorded, and I will be standing by should you need any assistance. It is now my pleasure to turn the conference over to Amy Agress. Please go ahead. Thank you, Nikki. Good afternoon, everyone. Thank you for joining us today. Our speakers today are Jack Abuhoff, CEO of Innodata, and Marissa Espineli, Interim CFO. Also on the call today is Aneesh Pendharkar, Senior Vice President, Finance and Corporate Development. 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 Q3. We'll then take questions from analysts. 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. 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 non-GAAP financial measures, including reconciliations of these measures with comparable GAAP measures. Thank you. I will now turn the call over to Jack. Thank you, Amy, and hello, everyone. The Q3 marks another leap forward for Innodata. We delivered record revenue of $52 million, representing a 136% year-over-year increase in organic growth. Adjusted EBITDA was $13.9 million, or 27% of revenue, which was five times our adjusted EBITDA in Q2, and our cash reserves increased to $26.4 million, up by $10 million from last quarter. We're very pleased with our results this quarter, and as a result of strong business momentum, we are raising our 2024 full-year revenue guidance. We now anticipate revenues between $52 and $55 million in Q4, which, if achieved, would translate to between 88% and 92% year-over-year growth for full year 2024. Our strong business momentum is reflected in revenue growth, margin expansion, broadening customer relationships, and continuing progress on our strategic roadmap. We are laser-focused on providing big tech companies with the data engineering they require to develop generative AI frontier models. We believe our efforts are paying off. In the Q3, we generated $30.6 million of revenue from just one of our big tech customers. Previously, we estimated that the programs and expansions we had won with this customer would result in approximately $110.5 million of annualized run rate revenue once fully ramped, which implies attaining $27.6 million in quarterly revenue once fully ramped. We are pleased to find that revenue received in Q3 from this big tech customer exceeded this estimate. We have seven other big tech customers as well, and we believe they will collectively become a significant part of our revenue makeup next year. They are all investing aggressively in generative AI. These seven other big techs include a prominent social media platform that we won in Q3. Like the other big techs, they are building their own traditional and generative AI models and leveraging Innodata for data engineering. We had mentioned last quarter that we expected this company would sign with us, and we're excited to report that they indeed have. We believe the initial value of the won engagements to be approximately $3 million in annualized run rate revenue at full ramp. Our confidence that these seven other big tech customers will collectively become a significant part of our revenue makeup next year is bolstered by the progress we made this quarter in building relationships, expanding work, securing new wins, gaining traction, and earning trust. The number of projects and pilots we have underway with these customers significantly increased in Q3 and are expected to increase in Q4. This includes several pilots running now, which hold the promise, potentially, of seven or even eight-figure wins. Last quarter, we also spoke about our pursuit of an agreement with an existing customer to colocate our staff at their sites. I'm pleased to report that we've signed this agreement and that we expect our resources to transition to working at one of their sites as early as next week. We believe colocating on customer sites positions us to further build trust and expand our collaborative relationship with customers as we look to capitalize on opportunities together. Additionally, last quarter, with another one of our big tech customers, we won new engagements projected to result in approximately $3 million in revenue based on our customers' projections. This followed the successful execution of two smaller projects. We are pleased to see the relationship growing, and we're in discussions with them on potentially other significant opportunities. In our last call, we also mentioned the possibility of engaging with another big tech customer, or big tech company, rather, which is one of the most valuable companies in the world and one of the companies most often talked about in connection with generative AI. Based on discussions, we now anticipate getting a pilot off the ground with this company in the next several months. We're also pleased to announce that in the Q3, we had our second win with the federal government, a deal to provide news briefs and media monitoring to a second federal government agency. Similar to our agreement with the first government agency that we signed last quarter, this new agreement will leverage the new generative AI capabilities we have built into our Agility platform. We are seeking to expand further into the public sector, and these federal sector wins are validating the success of that strategy. Now, let me talk a bit more about our go-forward strategy and opportunities for growth. Our strategy encompasses both services and platforms. On the services side, we intend to be a go-to partner for big techs that are building generative AI frontier models and enterprises that seek to transform their products and operations with generative AI technologies. We believe these are lucrative markets, which we are well-positioned to serve. On the platform side, we are utilizing our B2B industry platforms and enterprise platforms that leverage generative AI and traditional AI for particular niche use cases. McKinsey recently released research showing six distinct opportunities in the generative AI value chain, and it ranked services and applications as two of the three most attractive of these opportunities. Now, I'll give you some color on each of these three areas of focus for us. The first focus area is big tech. We believe we are still in the early days for big techs in terms of their generative AI investments. From recent disclosures, it's evident that these companies are seeing their generative AI investments yielding business benefits by enhancing current products and providing optionality for future growth and new products. Several of the big techs also signaled increased generative AI investment in 2025. In a report issued this past Monday, Morgan Stanley said they now see Amazon, Google, Meta, and Microsoft's combined CapEx reaching approximately $300 billion in 2025 and $337 billion in 2026 as they continue to invest in multi-year GenAI and LLM-enabled opportunities. A large component of this investment is training data. Big techs require two types of data for training large language models. The first is pre-training data, which is data that has historically been scraped from the web, and the second is supervised fine-tuning data, which is the data that is purpose-built by humans. Currently, most of the work we do for the big techs involves creating supervised fine-tuning data, which consists of instruction-tuning data, sometimes called demonstration data, and RLHF, or reinforcement learning from human feedback. You can think of instruction-tuning data as the data that teaches models to think, to respond to user prompts, to follow user direction, and to perform complex reasoning. This is data we create specifically for them. It is not web data or third-party data. We anticipate over the next several years, the big techs requiring progressively more complex demonstration data to support foreign languages, long context understanding, multi-modality, industry-specific models, and agentic capabilities. Models perform better when supervised fine-tuning data is high quality, large scale, highly consistent, and diverse. We believe Innodata will be at the forefront of providing this data. In addition to supplying supervised fine-tuning data, we are increasingly identifying opportunities to source and transform pre-training data. While today's models are mostly pre-trained on data scraped from the internet, this approach is likely to become increasingly problematic for two reasons. First, there are IP-related issues around the use of unlicensed third-party data with little legal precedent. Second, web scraped data is increasingly likely to contain the output of generative AI models, and training new AI models with data produced by AI models deteriorates performance of the new models, a phenomenon known as model collapse. We're also finding expanded opportunities in LLM safety and evaluation. We presently have six engagements in this area, and we're leveraging a lot of what we're learning from these engagements into a new platform that we're currently developing. In the past couple of months, we have demonstrated a prototype of our new platform to three of our big tech customers and several enterprises, and it has been well received. Our next focus area is enterprise services. On the enterprise side, our strategy is to provide a range of services to help businesses adopt enterprise GenAI. Our focus will be on integration and customization, providing strategic consulting services, AI services, digital services, and managed services, everything necessary to enable enterprise IT teams and business teams to drive a shift from legacy systems to AI-first solutions. We believe we are in the early days of enterprise generative AI investment and that enterprises are on the cusp of significantly increasing investment. And finally, our third focus area is enterprise platforms. On the platform side, we are working on B2B industry applications and enterprise applications for niche, specialized workflows in which humans apply knowledge and judgment in their interactions with unstructured data. One such application is Agility. We were particularly pleased with Agility's 26% year-over-year growth in the quarter and acceleration in new bookings. Before I pass the call to Marissa, I'd also like to say a word about the significant progress we have made this year in building a strong company with talent across key areas of the organization and a great workplace for our employees. We believe the work we have done on these fronts has been instrumental in enabling us to scale and meet or exceed the expectations of some of the most demanding, fast-moving companies in the world. This year, we have made several senior-level hires across delivery, technology, solutioning, pre-sales, recruiting, and sales and marketing. We have plans in place for additional strategic hires in Q4 and early 2025. In terms of brand building at a facility level, we have, for the second year in a row, been certified by Great Place to Work, and we are also certified as most preferred workplace and most preferred workplace for women by Team Marksmen. We also won an award for Asia Best Employer Brand 2024 by the World HRD Congress and Employer Branding Institute, and we were one of 10 companies to receive the 2024 Asian Leadership Awards. We also won the 2024 Trailblazer Excellence Award for pioneering leadership and innovative contribution to the IT business process management industry in terms of employee engagement, job satisfaction, culture and work environment, growth, development, and recognition. Two of our country managers received awards for their exemplary leadership. The National Awards for Excellence named us a Best Organization to Work for and also awarded us for our environmental responsibility initiatives, women's empowerment initiatives, and corporate social responsibility initiatives. I'll now turn the call over to Marissa to go over the financial results, after which Marissa, Aneesh, and I will be available to take questions from analysts. Thank you, Jack, and good afternoon, everyone. Revenue for Q3 2024 reached $52.2 million, reflecting a year-over-year increase of 136% and 83% on a year-to-date basis. On a sequential basis, we observed a 60% increase of $19.7 million from Q2 2024 revenue of $32.6 million. Adjusted gross margin for Q3 2024 was 44%, reflecting a sequential increase from 33% we achieved in Q2 2024. The comparatively higher gross margin in Q3 was attributable to the fact that we incurred $3.6 million of recruiting costs in the Q2 to support a substantial expansion of our organization to prepare for a significantly larger revenue base. Excluding the unusually high recruiting costs in Q2, adjusted gross margin in the Q2 would have been approximately 44%, consistent with the Q3. In Q3, these recruiting costs came down significantly to $500,000. Adjusted EBITDA for the Q3 was $13.9 million, or 27% of revenue, up from $3.2 million year-over-year in approximately five times last quarter's adjusted EBITDA. Net income was $17.4 million in the Q3, up from $371,000 in the same period last year and $0 last quarter. Our Q3 net income benefited by $5.6 million as a result of recognizing a deferred tax asset that related to our accumulated net operating losses, or NOLCO, and other deferred expenses from prior periods. Our cash position at the end of Q3 was approximately $26.4 million, up from $16.5 million at the end of Q2 and up from $13.8 million at year-end 2023. In the Q3, we did not draw down our $30 million Wells Fargo credit facility. The amount drawable under this facility at any point in time is determined based on borrowing-base formula. On our last earnings call, we reported a universal registration statement on Form S-3 with the SEC. On October 10, 2024, the SEC declared the registration statement effective, giving us the flexibility to sell up to an aggregate of $50 million worth of our securities in registered offerings. However, at this time, we have no specific plan to raise money. Lastly, as Jack mentioned, we are raising our 2024 full-year revenue guidance. We now anticipate revenues between $52 and $55 million in Q4, which, if achieved, would translate to between 88% to 92% year-over-year growth for full year 2024. Thank you, everyone, for joining us today. Nikki, please open the line for questions. And at this time, if you would like to ask a question, please press the star and one on your telephone keypad. You may withdraw your question at any time by pressing star two. Once again, to ask a question, please press the star and one on your telephone keypad. We'll pause a moment to allow questions to queue. And we'll take our first question from George Sutton with Craig-Hallum. Please go ahead. Your line is open. Thank you. Jack, obviously an outstanding quarter. Congratulations, so I was thrilled with the results in the quarter, but frankly, even more thrilled with the ability to guide for the same revenue in Q4, which is obviously suggestive of both your number one customer staying very large, but I wondered if you could just give us deltas quarter-over-quarter as you think through the composition of the equivalent revenue growth in Q4. I'm sorry, George, well, first of all, welcome to the call. Thank you very much. Maybe you could just restate the question a little bit for me. I wasn't quite following what you're looking for. You're guiding to Q4 revenues equivalent to Q3. Yes. Q3 was historic, so I just want to make sure I understood what kind of deltas we should anticipate within that number from Q3 to Q4. Is it the large customer taking the same amount? Is it new customers coming in with initial programs, which ultimately could give us some upside potential? Just trying to get a sense of the delta. Got it. Okay. Thank you. So I think that, obviously, there are a lot of moving pieces. What we're very enthusiastic about is first, with our largest customer, we see them continuing. We see the opportunity for them to grow and expand in 2025, actually. As we look out over Q4 and next year, what we see is a lot of momentum. And we've seen that momentum in Q3. We see that momentum continuing in Q4. We measure that momentum in terms of relationships, trust, but also in terms of expansions, pilots, new wins, traction. We're confident in saying that we believe now that that group of companies is collectively going to become a very significant part of our revenue makeup next year. In terms of Q4, we think that we'll start to see that, but we believe that it'll become even more prominent in 2025 and help us drive continued growth. So a question as I read through the large GPU users for training models, what they're talking about is, yes, we're spending billions on GPUs, but what we need to spend more on is the ability to create new use cases for the AI. And the way we do that is we have to train the data. That's the data engineering part of that. That is exactly what you do, correct? So I just want to be clear when we read these transcripts of some of the players in the space making these very eloquent logical reasoning why they're spending so much now on data. I believe that's exactly what is benefiting you, correct? That's exactly right. Where the action is in terms of building out those capabilities is in supervised fine-tuning data. There's no aspect when you think about compute and algorithms in addition to data as the key ingredients for the models. We don't believe that there's any ingredient that is as critical to high performance and to building out those use cases as data, and when we look at the trends that will be taking place in data and the requirements in order to train for domain specificity, multimodality, more complex reasoning capabilities, agentic capabilities, it all comes back to data, and we're very excited about that. We're doing a lot of work internally to make sure we're prepared for those needs, doing a lot of experimentation work that's going to continue into next year as well. So we think we're very well positioned to continue to serve their needs as their needs continue to form around those things that you're referring to. Super. I'll turn it over to others who can come up with other adjectives for the quarter. Great. Thank you, George. Thanks so much. Thank you. Our next question comes from Alan Klee with Maxim Group, LLC. Please go ahead. Your line is open. Yes. Hi, and congrats on a strong quarter. You mentioned that your recruiting costs came down. Do you feel like the costs? Could you talk a little about your direct costs, and do you think that is kind of a good run right now, or is there a reason why that may grow at a different rate than revenues? Sure. So I think first, again, Alan, welcome to the call. Thank you for joining. I think that the recruiting costs will somewhat be a function of what we see coming down the pike. At the same time, we're looking to manage those down by having established strong internal recruiting capabilities that are enabling us to drive the unit costs of recruiting down quite considerably. In the quarter, our recruiting costs were $500,000. We were expecting $300,000, but in light of the growth that we see coming, we were happy with the $500,000. Going forward, again, I think it'll be somewhat responsive to what we're seeing has been modified by what we're able to do internally. Thank you. And one of the things that stood out to me is if I looked at your operating expenses year-over-year, excluding direct costs or your other. I wrote it down. I don't have it in front of me. Something like it was up only 33% versus your revenues up significantly higher. So very good operating leverage to the bottom line. So the reason I'm mentioning that is I know as you're growing, you're also going to have to spend more, but how do you feel about on the operating expenses, the ability to continue to get operating leverage? Yes. I think we're going to continue to see great operating leverage. As you said, in the quarter, sequentially speaking, we were up, I think it was $19 million on the revenue side. And if you adjust for the recruiting costs, I mean, you take them out of Q2 and Q3, the delta on adjusted EBITDA was about $8 million. So that's suggestive of 40% flow-through, which 41% flow-through, which is great. One of the very attractive things about the big tech market is, of course, the spend and the projected CapEx. For us, in addition to that, it's very efficient from an OpEx perspective in terms of go-to-market. You have deep wells of spend. You have to build those relationships out. You have to service them well. But you don't need a giant sales organization in order to do that well. You need talent. And I think I continue to see that as a driver. At the same time, in 2025, and we're thinking a lot about how we leverage where we've gotten to and where we go with this, we've got an exciting 2025 plan. We have an incredible team, incredible energy right now as a team. We're preparing to launch our plan internally at a global offsite in Athens in January. We're very much thinking out of the box. We're thinking about where we can go from here. I think we've made some hires that are super critical. We brought on just this week another high-level PhD in AI and machine learning who's going to be helping us along that path. Incredible talent. We're encouraging the team and each other to think outside the box. I'm optimistic that some of the most exciting things that we might come up with over the next year haven't even been things that we've talked about yet or put on display. So very exciting times for us. As you said, a very efficient model where we get the benefits of that operating leverage and enable ourselves to expand and do things strategic for the company. Thank you. And then, I mean, two key factors for your growth are just the demand outlook, which I believe is going to definitely be there. And then also critical is that you keep the quality of what you're doing so that you keep winning the business competitively and keeping the business. So can you talk a little about what you've done and will be doing to make sure that the quality of what you offer is top-notch? Sure. There's no single factor that's more critical than data quality. We've created and borrowed from our legacy a lot of processes and capabilities in terms of driving quality and consistency that have benefited the largest information providers in the past and are now benefiting the big tech companies that are using the data not for information products, but in order to train models. Next to data quality and what we've clearly established with our largest customer is we became the choice for their engineering teams in terms of a data engineering partner on quality. But in addition to quality, it's agility. It's the ability to work hand in glove with the engineering teams, responding to where they're going, responding to the needs of the model as the model is tested and retested for the attributes that they're building on. And we think we've distinguished ourselves on that front also. So we've got the relationships in place. We've got the capabilities in terms of data quality. We've got the practices in terms of agility. And we think we're seeing the benefits of that in growing momentum at all of the big tech customers and excited about 2025 and where this goes. That's great. My last question is on agility. Good growth there. Could you talk about some of the initiatives you have going on there? So on the Agility side, we're all in on generative AI. We've taken the workflow that spans identifying prospects for distributing news to all the way through to monitoring pickup and monitoring the issues that people care about to analytics. And we've infused the technology in several aspects of that in a very seamless way, in a very well-integrated way. And we have more to come. And what we've seen as a result of that is that our win rate and demo to win has significantly increased. We're winning more market share. Analysts are now rating us based on a whole lot of factors as well as AI integration. We're off the charts in terms of AI integration. And we're winning on, I believe, most all of the other criteria as well. So we're very excited about where that business is taking us. That's great. Thank you and congratulations again. Thank you. Thank you. Our next question comes from John Katsingris with Wedbush. Please go ahead. Your line is open. Hi. Thanks so much for taking the question and congrats again on a great quarter. So looking into recent federal wins and, I guess, contrasting that to the enterprise opportunities that you guys are executing in the field, what do these engagements mean for Innodata's broader strategy? And how can we look at that relationship between the two, I guess, longer term from the bird's eye view? Thanks. Sure. A great question. So the work that we've talked about last quarter and this quarter is on the Agility side. It's a very sharp edge of the wedge in terms of bringing immediate value to the agencies that we're working with. We've got a lot of distinguishing capabilities there. We believe that we will be able to continue to expand the importance of that market. We don't see that as something that's going to contribute necessarily in an extensive way in 2025, but we plan on making inroads. And we think that that will be likely a contributor as we go forward beyond that. We believe that the federal government is making significant investments in the technology and is likely to now increase the level of those investments and increase their focus on winning in that sector. And it's our goal to figure out the space, figure out how we work in that space, and build our business there. Got it. Thank you. Thank you. Our next question comes from Hamad Khorsand with BWS Financial. Please go ahead. Your line is open. Hi. So my question was, how have you been in the conversations with your other large tech companies as far as being able to scale as fast as possible, just like your largest customer? So a few things that we see there. Firstly, that all of these customers have significant spend, significant ambitions. We find that we're competing largely with the same other companies. And that's why we're optimistic that the playbooks that we've executed and the capabilities that we've brought to the largest customer will be valued in a similar way with these others. We've seen a lot of momentum building in terms of the vectors that we track. So we track as a vector relationships of trust, expansions, new wins. We track as a metric the POCs and small projects that are then leading to larger projects. And we see all of that really forming up exactly the way that we were hoping that it would. And that's giving us the confidence to say that we believe those companies will be a more significant part of our revenue next year. Great. Thank you. Thank you. And we show no further questions at this time. I will turn the call back to Jack Abuhoff for closing comments. Great. Thank you. So yeah, we're thrilled with our results this quarter. We've really never felt more excited about our business and our ability to execute our strategy with the current market opportunities that we're seeing. We believe generative AI is a transformative technology that's still in its earliest innings, that high-quality training data will be among the most important contributors to high-performing frontier models of the future. And we believe that we are and will continue to be ideally suited to support big tech companies who are building these models and enterprises that are adopting them. So again, thank you all for participating in the call today. Q3, obviously, it was a record quarter. We're very proud of what we've accomplished, but we're equally excited about where we're going. Thank you. Thank you. And this does conclude today's program.