Good day, everyone, and welcome to the Innodata second quarter 2023 earnings call. At this time, all participants have been placed on a listen-only mode, and we will open the floor for your questions and comments after the presentation. If you have any questions or comments during the presentation, you may press star one on your phone to enter the question queue at any time. It is now my pleasure to turn the floor over to your host, Amy Agress. Ma'am, the floor is yours. Thank you, Matthew. 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 Maritz will follow with a review of our results for the second 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 statements include, without limitation, any statements that may predict, forecast, indicate, or imply future results, performance, or achievement. These statements are based on management's current expectations, assumptions, and estimates and are subject to a number of risks and uncertainties, including, without limitation, the expected or potential effects of the novel coronavirus pandemic and the responses of governments, the general global population, our customers, and the company thereto. Impacts resulting from the rapidly evolving conflict between Russia and Ukraine, investments in large language models, that contracts may be terminated by customers, projected or committed volumes of work may not materialize, 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 markets, particularly new and emerging markets, that our services and solutions support, continuing Digital Data Solutions segment revenue concentration in the 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 deriving 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 breaches, cyberattacks, privacy breaches, or data breaches that result in the unauthorized disclosure of consumer, customers, employee, or company information or service interruptions, and various other competitive and technological factors, and such 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. Actual results could differ materially from our current expectations. Thank you. I will now turn the call over to Jack. Amy, thank you. Good afternoon, and thank you for joining our call today. I am tremendously excited to have announced today that we landed yet another of the Big Five global tech companies as a new customer to help it train and scale generative AI and large language models. These, of course, are the technologies behind ChatGPT and Stable Diffusion, technologies that have caught the world by a storm and set off what we believe will be the next revolution in computer technology. We expect our formal agreement with this new customer to be signed tomorrow. With today's deal announcement, we are proud to say that we have won each and every one of the potentially transformative pipeline deals we spoke about last quarter. As a result of these wins, we are poised to support AI and large language model development for four out of five largest tech companies in the world. These wins, including the deal we are announcing today, have all come in just the last eight weeks, so they are not yet reflected in our financial results. We believe that these wins are potentially transformative for our company. Moreover, we believe that we are in the very early stages of exploiting a market opportunity, which itself is in its very early stages, and for which, as our last eight weeks have wins demonstrate, we believe we are particularly well suited. In today's call, I'm going to provide some updates and additional perspective around today's announcement and the other deal announcements we made in the last eight weeks. I will discuss the opportunity landscape we see forming around generative AI technology and how we intend to exploit it. Lastly, I'll review our Q2 results and provide some forward guidance. Let's start with the deal announcements. In the last eight weeks, we made four deal announcements, including the deal we announced today. Two of the deals are with an existing customer, and two are with two new customers, all of whom are among the top five global technology companies in the world. I'll briefly review each of these, starting with today's announcement and then working backwards in reverse chronological order. For the new customer we're announcing today, we expect to be providing an array of services required to build and scale large language models. We expect to begin ramping up the engagement early in the fourth quarter. Importantly, the agreement we expect to sign tomorrow with this new customer is a framework agreement that enables the customer's business units to easily add additional programs and allocate additional scope and spend to us. The customer has told us that it will be potentially requesting us to participate in additional programs, which may include supporting the customer's own customer base with model fine-tuning and integration. Under the agreement, we expect the customer to authorize $3.5 million in spend to get us started, and the customer has stated that it intends to supplement this authorization as we move forward. It has shared with us its vision for the initial program, which, if fully realized, we believe could potentially result in approximately $12 million of new quarterly revenues at maturity. That said, at this point, we do not know when or if the initial program will reach this level of spend. In addition, while the customer has told us we will be signing tomorrow, it is possible that this could slip as it is outside our control. On July 18th, we announced having won another new customer, another of the top five global tech elites. Similarly, we will be helping this new customer develop and train large language models. The customer shared with us that it had been extremely impressed with our pilots and selected us from a field of 17 competitors. The agreement we signed with the second new customer provides for up to $8 million in spend for the remainder of 2023 under an initial program, although how much of this we recognize is dependent upon a number of factors, including how quickly we ramp up. Ramp up aside, based on discussions with this customer, we believe we may potentially get to an annualized run rate of $15 million with this customer by the end of the year, solely on this initial program. The agreement we signed with this customer is also a framework agreement, which enables its business units and product centers to easily assign new programs and scope to us. We've already begun discussions with this customer regarding new programs. On June 27th, we announced that an existing Big Five customer had selected us to perform AI data annotation and LLM fine-tuning as a white-labeled service for its cloud and platform customers. We view this as a particularly strategic win, as we believe that it gives us the potential ability to scale LLM services for enterprises in a way that would have likely been impossible working solely under our own brand and with our own sales and marketing. Driving distribution under the customer's brand is a uniquely attractive opportunity, the strategic value of which I will talk about more in a few minutes. The engagement builds on our 18-month relationship with this company, under which we are told we have distinguished ourselves based on data quality, responsiveness, and agility. While we stated in our June 27th press release that we expected to kick off the program with three end customers in July, I'm pleased to report that we already have nine end customers signed on for pilots, and we are not even halfway through August. We believe three of these pilots are likely to turn into booked business near term, with 1 having an anticipated booking value of over $1 million. Beyond these 9 white-labeled enterprise pilots, we presently have a direct pipeline of enterprises with which we are now or soon to be engaged in discussions about LLM fine-tuning and integration. Our direct pipeline includes a large legal information company, one of the largest life insurance companies in the world, a leading investment bank, and a leading commercial bank. In the near term, through this program with our customer, we anticipate a cadence ofone to two new pilots each week. While it is difficult to forecast the revenue opportunity this program represents because it is so new, if we can continue to onboard from the potential pool of tens of thousands of our customers and customers at the pace we're executing currently, we believe this opportunity could dwarf any single initiative we are now pursuing. On June 14th, we stated that an existing Big Five customer had engaged with us for its LLM build program. In that announcement, we stated that we anticipated potentially exceeding $8 million in revenue this year with this customer. This is up from approximately $3 million last year. We believe there could potentially be considerable opportunities to expand existing programs with this customer and to land new programs. The June 27th announcement I just spoke about regarding the white-labeled service is an example of such a new program. I would like to now discuss our opportunity landscape and to contextualize these wins within a strategic framework. First, we believe that a technology revolution is before us, that it is in its very earliest of days, that it will drive profound changes in the way people work and engage with technology. Looking back, we initially became convinced that we could gain a toehold in the emerging generative AI market by pivoting off our experience, creating high quality, domain-specific data, and our seven years experience in training AI models. We selected the Big Five as our initial target market because we predicted that they would be early adopters and would be spending aggressively. They all have products, including search, ad serving, and productivity tools, that we believe stand to benefit directly from generative AI, and several are hyperscalers that would seek to provide the high-performance infrastructure for training and serving a range of generative AI models. Fortunately, based on what we've seen to date, we believe our assessment was accurate. In their Q2 analyst calls, several of the Big Five tech companies referred to generative AI and LLMs as at the core of their innovation plans, backed by commitments for billions of dollars per year of capital expenditures. At least one prominent firm stated that every one of his businesses had multiple generative AI initiatives. We believe it is quite clear that these companies are now in a race to build cutting-edge LLMs that can serve as a foundational layer of generative AI to serve their products as well as their ecosystem customers. It is early days. One company described it today, or one company described it as today being just a few steps into a marathon. For the Big Five tech companies, we expect to be performing a range of data engineering work required to build cutting-edge generative AI. We expect this to potentially include collecting data, creating data sets used to train the models and teach the models to follow instructions and chain-of-thought reasoning, providing reinforcement learning, the process by which we align models with human values and complex use cases, and providing red teaming and model performance evaluation. Over time, we anticipate working with these companies to address multiple languages, multiple data domains, and multiple data modalities, including video. Given that we have now successfully penetrated four of the five largest technology companies, we believe we are poised to potentially drive significant growth in the market in the near, medium, and long term. It is worth mentioning that beyond the Big Five, there are another 50- 100 technology companies that we estimate are now building or likely to be building their own LLMs. This includes some prominent, well-funded startups. We intend to build relationships with these companies as well. I mentioned a few minutes ago another compelling opportunity for us with the Big Five, establishing white label programs under which they can provide our services to their customers under their brand. We've now got such a deal in place with one of the largest hyperscalers in the world, and we are exploring similar opportunities with others. We view the white label arrangement as a particularly strategic opportunity for three reasons. First, given that this customer is one of the largest global cloud providers, we expect many thousands of customers and partners to utilize their infrastructure for generative AI. These customers will likely find a one-stop shop for all things AI to be an attractive value proposition. They will be able to obtain compute, storage, foundation models, machine learning, database, and data services, basically everything required to train and serve generative AI, all under one roof and at an attractive price point. Second, in a mid-market companies such as ours, growth is typically constrained by the size and scale of the sales and marketing effort. These white label programs offer us a means of potentially scaling independent of our own sales and marketing, leveraging both their brands and their customer reach. Lastly, as a result of these programs, we believe that we are likely to gain early exposure to a wide range of early adopter generative AI use cases. Under our initial white label program, we have recently piloted use cases ranging from call center summarization, legal and medical question answering, and e-commerce. We believe this exposure will set us up well for what we believe will be our largest and most significant opportunity, LLMs for the enterprise. We believe that a decade from now, virtually all successful businesses will be AI companies, and that between now and then, the pace of adoption will be dramatically accelerating. We believe there are essentially two reasons for this. First, LLM early adopters are likely to be significantly more productive and to create significantly more compelling customer experiences. Thus, there is likely to be strong competitive pressure accelerating the adoption curve. In a June study, McKinsey estimated that generative AI could add $trillions in value to the global economy, with half of all of today's work activities automated sometime between 2030 and 2060, with a midpoint of 2045. Secondly, the tech stack will be ready. High-performing, commercially usable, open source, generative AI models will become increasingly available, and the best performing closed source models will likely support fine-tuning on proprietary data. We anticipate that this will make it possible for companies of all sizes to customize their own large language models and to build generative AI applications in secure and enterprise-grade fashion. As the enterprise market accelerates, we believe our capabilities will be increasingly in demand. Our plan is to exploit the enterprise opportunity with what we believe are five distinct competitive advantages. First, the skills and referenceability we will have acquired, helping the Big Five build the very foundation models with which enterprises will then be seeking to integrate. Second, the experience we will have gained across a wide range of use cases, working with early adopter enterprises through our white labeled arrangements with the hyperscalers. Third, the real-world experience we continue to gain in integrating both classical and generative AI into our own operations and our own products. Fourth, our technology platforms for transforming enterprise data into LLM-ready context for both model fine-tuning and prompt injection. Fifth, our technology platforms, both existing and roadmap for development, that will help enterprises generate reliable, fact-based responses and insights from foundation models using techniques such as Retrieval Augmented Generation, or RAG for short, that combine the reasoning and language engines of pre-trained LLMs with a business's proprietary context data. Unstructured data like technical documents, images, videos, and reports, as well as structured content from enterprise systems and sensors. In addition, our strategy is to harness AI and LLM technology into specific workflow applications. For example, in May 2021, we announced a multiyear agreement with one of the world's largest banks to use AI to reengineer workflows related to scanning regulatory updates. This effort is now well underway and is being enthusiastically received by the bank. It holds the promise of improving regulatory change management, resulting in reduced fines and penalties, while also reducing the heavy lifting done by people today. Under the arrangement, the bank pays us an annual subscription fee. We're now in discussions with three other companies about this product. Let's now talk about what to expect financially as a result of our new wins. We are expecting to begin work on the win we announced today in early Q4. On the win we announced on July 21, we kicked off work about two weeks ago. Based on our experience, engagements start slowly. First, we work with the customer to create detailed specifications and run pilots to ensure that the specifications are yielding the intended results. Oftentimes, this requires several iterations. Once the specification is locked down, we then put in place the required infrastructure. This includes custom configuring technology systems, finalizing process designs, and assembling human resources, data engineers, and subject matter experts. This can take 2 to 3 months. After this is completed, we scale up. We typically scale up slowly so that we can continue to test and refine as necessary with the customer. We expect our programs to be dynamic, with customer dependencies and checkpoints throughout, which makes it tough to do quarterly forecasting at this point. Based on our experience, the end result that gets us to a full ramp-up is typically achieved in a roughly 12-month period. Finally, let's talk about our Q2 results and guidance. In Q2, revenue was $19.7 million, a 4% increase from Q1, and adjusted EBITDA was $1.6 million, a 100% increase from Q1, which we believe was made possible by the work we did late last year and into Q1 in sharpening our focus and finding opportunities to operate more cost effectively. Please note that there was no revenue in the quarter from the wins we discussed today. It is also worth noting that there was no revenue in the quarter from the large social media company, which contributed $2.5 million in revenue in Q2 of last year, but dramatically pulled back spending in the second half of last year as it underwent a significant management change. If we back out revenue from this large social media company, our revenue growth in the quarter over Q2 2022 would have been 13%. We expect that revenue and adjusted EBITDA growth to accelerate from here in the ensuing quarters, both sequentially and year-over-year, as the wins we've discussed today start ramping up. We ended the quarter with $13.7 million in cash and short-term investments, up from $10.8 million at the end of Q1. We continue to have no appreciable debt. In order to support our growth and working capital requirements, in the quarter, we put in place a secured revolving line of credit with Wells Fargo that provides up to $10 million of borrowing, subject to a borrowing-based limitation. I'll now turn the call over to Mariz to go over the numbers a bit more, and then we'll open the line for questions. Thank you, Chuck. Good afternoon, everyone. Allow me to recap the Q2 2023 financial results. Revenue for the quarter ended June 30, 2023, was $19.7 million, compared to revenue of $20 million in the same period last year. The comparative period included $2.5 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. There was no revenue from this company in the quarter ended June 30, 2023. Net loss for the quarter ended June 30, 2023, was $0.8 million, or $0.03 per basic and diluted share, compared to a net loss of $3.8 million, or $0.14 per basic and diluted share in the same period last year. Revenue for the six months ended June 30, 2023, was $38.5 million, compared to $41.2 million in the same period last year. Again, the comparative period included $6.9 million in revenue from the large social media company referenced above. There was no revenue from this company in the six months ended June 30, 2023. Net loss for the six months ended June 30, 2023, was $2.9 million, or $0.11 per basic and diluted share, compared to a net loss of $6.6 million or $0.24 per basic and diluted share in the same period last year. On adjusted EBITDA, adjusted EBITDA was $1.6 million in the second quarter of 2023, compared to adjusted EBITDA loss of $1.2 million in the same period last year. Adjusted EBITDA was $2.4 million in the six months ended June 30, 2023, compared to adjusted EBITDA loss of $2.3 million in the same period last year. Our cash, cash equivalent and short-term investments were $13.7 million at June 30, 2023, as compared to $10.3 million at December 31, 2022. Again, thanks, everyone. I'll turn you over to Matthew. We are now ready to take questions. Certainly. Everyone, at this time, we can conduct a question-and-answer session. If you have any questions or comments, please press star one on your phone at this time. We do ask that while posing your question, please pick up your handset if you're listening on speakerphone to provide optimum sound quality. Once again, if you have any questions or comments, please press star one on your phone. Please hold while we poll for questions. Your first question is coming from Tim Clarkson from Van Clemens. Your line is live. Hey, Jack, good quarter, you know, everything I hope for. Just a basic question. It seems to me, looking at the results, that your breakeven would be somewhere around, I don't know, $21 million-$22 million. Is, is that kind of a ballpark number? Yes, Tim, I think that's right. You know, as, as I mentioned in, in my remarks, we did a lot of work late last year into Q1 to, you know, focus ourselves and focus our investments and, and, achieve, you know, yet a, a higher level of operational and excellence and productivity, and, and that's benefiting us now. I, I think that that's right. Okay. Now, historically, you know, Innodata's strength has always been execution. I mean, you know, when we've had problems, it's been, you know, contracts ending, being project-based, so on. In terms of execution, I, I can't remember, you know, a screw up on that end. How hard are these contracts that these new contracts to execute? Are these within the, the, obviously, the competency of the company, or how risky are they? Sure. Well, let me start by saying that they're squarely within our competency, and that's why we're so excited. I mean, we've, we've got the ability to. Well, we're finding ourselves, well, you know, squarely in the middle of the, you know, the biggest technology revolution of our lifetimes. We're finding that we've got the competencies that are, you know, highly applicable to driving that forward. We're working with the companies that are gonna be spending $ billions of CapEx to do just that. That said, I think the contracts are hard, but that's why, you know, it's good business for us. We are good at executing. We have a track record of executing some of the hardest data products and projects that have, you know, been apparent over the last, you know, couple of decades even. We're finding that we are, you know, several weeks into executing some of these new deals, but we're already demonstrating the excellence that we bring to that. The customers are very, very happy. We're excited. We're excited about where we are. We're excited about the opportunities we have, we're excited that we're bringing the competencies that we've had historically to a new market that highly values them. We expect things to go very, very well. Right. Right now, how would you if someone was looking at Innodata from the outside, how would you articulate the competitive advantages that, that you guys have? I think we've, we've, you know, got quite a few. You know, I, I think that the work that we've done in the past, as I said, you know, creating high-quality data and, you know, building AI models and, and, you know, building and integrating them in the wild, meaning outside of, you know, research labs and academia. It's perfect. You know, we've been, like, training for today for the past, you know, five years. Now it's, you know, the big game, and I think we're, you know, completely prepared for it. Some of the competitive advantages that we're bringing, you know, to the table now are, are, you know, breadth of domain expertise, you know, competencies in AI, model building and, and, and data training, geographic spread, you know, ability to, you know, to, to create very high-quality training data. That's exactly what, what is in order. As we look forward, what we see is we're building additional competencies. As I mentioned, you know, a few minutes ago, we're now helping build foundation models. We're now, you know, developing experience in a wide variety of use cases, are expecting to develop a wide variety of experience through the white label programs that we've talked about. We're continuing to build, you know, still additional real-world experience in terms of, you know, integrating classical and generative AI into operations and products. All of these are, are, are proving to, to create significant competitive advantage for us in the market. Sure. Now let's pretend that at some point, these contracts start to come to reasonable fruition, and you're hitting, say, around $30 million in revenue. At that level, what kind of pre-tax margin would you guys be showing? I think the, the way we would guide people in terms of building out models is to, you know, think about an adjusted gross margin, meaning, you know, gross margin less, you know, severance, you know, G&A and, and stock option costs. Think about an adjusted gross margin as we scale of, you know, between 40%-45%. In terms of SG&A, you know, we've got a tremendous market opportunity in front of us to exploit that. We're probably gonna be adding a, a bit more in sales and a bit more in terms of, you know, program execution, but not a ton more. you know, our business is not tremendously capital intensive, so, you know, I think, I think you can kind of, kind of drag that out and, you know, predict what kind of cash flow we're gonna be able to drive. Should be at least a 10%-15% pre-tax once you get above $30 million. That's what I'm thinking. Yeah, I, I, I think that that's absolutely right. I think that there's potential to improve on that. Sure, sure. Okay, well, I mean, you know, everything is, is going great, obviously. You know, I'm just thrilled and, and, you know, it's still so early. I think that's the exciting part of it. I'll let other people ask questions. Great quarter. Thanks. Thank you. Thank you. Your next question is coming from Dana Buska from Feltl and Company. Your line is live. Hi, Jack. Hey, Dana. How are you this evening? We're, we're doing great. Thank you. You're welcome. Everything sounds like it's it's going pretty good. I have a couple questions, around your white label program. Could you explain, a little bit about what exactly you mean by white label? Sure. What I mean is that we're going to be performing data engineering services standing behind the brand of one of our large customers. Again, we see this potentially expanding to other customers, but right now, it, it, it's one of them. It's a customer that, that, that markets, you know, compute, you know, storage, foundation models, you know, database. We'll be marketing now, in addition to that, data services. A customer of theirs that is looking to create or build or fine-tune generative AI models will find, we believe, will find it attractive to be able to obtain all of that in one place. When they obtain data services, we're, you know, we're, we're gonna be providing some of that. Okay, excellent. Around that, are you gonna be relying on their sales force to do that, or is it you, you're having your sales team be involved with those type of projects? No, primarily we're relying on their sales force, certainly in this first, you know, iteration. Again, that's what's so attractive about it for us, that, you know, we have the opportunity to scale independent of, the, the limitations that, you know, our sales and market reach impose upon us, and our brand recognition imposes upon us. This is a very highly regarded brand with tens of thousands of customers, and I think potentially this program, and perhaps others like it, will enable us to, you know, achieve an escape velocity that otherwise wouldn't be possible, just working through our own brand and our own sales marketing. Okay. That's, that sounds, that sounds pretty impressive. Along those lines then, will, like, price negotiation, that'll be all done through your clients, and you guys won't have to deal with that, or, or will you be, more subject... Well, let me ask, how do you see the pricing going with the product? We're able to provide pricing upfront to the customer, who's then able to represent that pricing in discussions with its end customer. Okay.... Okay. Then, you didn't really talk much about or at all about Synodex or Agility. Those two seem to have had nice quarters. Could you elaborate a little bit on those two businesses? Yeah, happy to. You know, there's just, you know, really so much to, to talk about in terms of, you know, what's going on in the business that, you know, we were already probably, you know, beyond some people's attention spans, so we left a few things out. But, you know, what's going on in Synodex and Agility is, is very, very impressive, and we're, we're very happy with the performance there. You know, Agility, we had a year-over-year growth of 13%. We returned to adjusted EBITDA positive in the quarter. You know, we, we, we look at it like, you know, we're now making money there. Again, we had solid bookings. Our, our gross retention levels were actually beyond, you know, what we had targeted in terms of our internal planning. And we're seeing, you know, improvements on our average selling price and in our sales cycle, in part, you know, attributed to the work we've done, you know, integrating our new product, PR CoPilot, into, into that platform. PR CoPilot is, of course, a AI-powered or generative AI-powered capability that allows people to gain, you know, AI augmentation, AI assistance in generating market pitches or PR pitches and, and press releases. You know, very, very happy with what's going on there. On Synodex, you know, over the past year, we've had some problems in Synodex, mostly related to kind of COVID and, you know, some, some attrition issues that we attribute to, to, to COVID, but we're, you know, we're nicely digging out of that. We had an increased gross margin for the second consecutive quarter, a positive gross margin for second consecutive quarter. We are working with two of our largest customers, kind of charting out new products, including some automated products, which is very, very exciting. We're happy with that business as well. Excellent. Yeah, they do both look like they're going along well for you. Just to go back to your, to DDS, could you talk a little bit about capacity with all these new projects that you have? Would you need to be adding capacity, or do you have the capacity already available? In combination, we've, we've got the engineering capabilities and the, you know, performance management capabilities and, and, you know, things like that, that are required. We add human resources, you know, as, as and when needed, but we don't have any issues relative to, you know, scaling around that and adding, you know, resources kind of just in time when we need them. Okay, wonderful. That, that does it for me. Congratulations on having things go so well. It looks very impressive to me. Thanks. Thank you, J. Thank you. Once again, everyone, if you have any questions or comments, please press star then one on your phone. Your next question is coming from Bruce Galloway from Galloway Capital. Your line is live. Hey, Jack, congratulations. Great quarter. Looks like you're firing on all cylinders. In the past, you spoke about growth rates and net margins, you know, going forward, like two or three years. I guess you stopped when, when the world stopped. Are you gonna be giving us some guidance, you know, going forward along those lines? Also, now that you're doing so well and you're sort of in the middle of the groundswell, are you gonna be getting any Wall Street coverage? Sure. Bruce, good to hear from you. Thank you for joining the call. The answer is, you know, we, we've, we've given some guidance in terms of, you know, we're expecting year-over-year and sequential growth in terms of both revenue and adjusted EBITDA as we ramp up these, these programs. We also talked a lot about how there's uncertainty in timing of ramp up over the next, you know, few months, and for that reason, we're kind of, you know, we're, we're staying with the guidance that we've given previously in terms of, you know, adjusted EBITDA going forward and, and such. We're giving some guidance on, on what we expect gross margin up to, to be. What's, you know, so, so interesting about the opportunities that we've got in front of us is all of the contracts, virtually, that we're entering into are framework agreements, and there's a lot of talk about expanding programs. There's a lot of talk about some of the programs that we're, we're now initiating to themselves be expanded very significantly. All of that is fairly dynamic. We're, we're, we're not really on solid footing, given the ramp-up and given all of the talk of expansion, to provide, you know, significant detailed guidance going out. You know, I think the important things are that-... You know, frankly, I never thought we would be in a position to say, you know, we're now working with four of the five Big Five companies who are, you know, investing $ billions of CapEx into, you know, the technology that, you know, we're poised to help them with. You know, it's so clear to us that there's a gold rush happening, and we're the ones with the picks and shovels. You know, I think we're going to see the quarters lay out, you know, very, in a very compelling way. Being able to forecast them with precision is difficult at this point in time. You know, we're working very hard to stay on top of the opportunities and land and expand. I think that should be our focus rather than trying to become experts at, you know, forecasting with precision right now, given the magnitude of what's going on. What about getting some Wall Street coverage? I mean, you got an exciting story to tell. Let's tell it. Yeah, you know, there are a couple of analysts that we're in conversations with. We'll see where that goes. I think that could be, you know, something that comes our way. It's not within my control, of course. You know, as you know, we haven't, we haven't done, you know, a raise. We're, we've been able to accomplish what we've accomplished working, you know, with internally generated, you know, cash flows and making investments from that. You know, a lot of times coverage kind of, you know, comes with investment banking activities. But again, that said, you know, there are a couple of people that have been in conversations with us. Okay. Al-also, the comment you made about the generative AI-focused IT services going from $87 million- $82 billion in 11 years, 12 years. I mean, could, could, could you elaborate on that? You know, that-that's like hyper, hyper growth, and where do you stand within those IT services? Yeah, I think we're a player, and I think we're going to become, you know, it's, it's our, it's our intention from a mission perspective to become a significant player. I think we're already demonstrating that we are. You know, I'm happy to send you, you know, a URL for that report. It's a Bloomberg report, came out recently. Numbers are exciting, you know, certainly what we've been able to do over just the last eight weeks, perhaps in, in its own way, you know, supports the hypothesis that they're driving toward. All right, it sounds exciting. It, it very much is. Thank you, Bruce. Thank you. Your next question is coming from Tim Clarkson, from Van Clemens. Your line is live. Yeah, just one follow-up question, Jack. I know that you have sold stock before in Innodata stock, so it's not something that you're- you've never done. I've noticed you haven't sold any stock, say, in the last couple of years. I assume, you know, you're, you're vested in this belief that things are gonna be really good. Yes. Well, Tim, I've we've been working at this for a long time. As I said, I think we made some, you know, very good decisions that got us to the point where we are today. I think that we're, you know, square in the middle of something that is so big and so prominent and we're so perfectly suited for it, that it's extremely exciting. In terms of, you know, selling stock, I don't know. I mean, I wouldn't think that investors should look at insider stock sales as a means by which to predict the future. I think that there are people who have their own needs and reasons for, for needing to, to, you know, raise a little bit of money here or there, or to, you know, diversify their exposure, and I think that's perfectly fine when they do it. That doesn't mean that they're not completely vested in the success that we're driving, and as I think we're, we're now demonstrating. Right. My point is, you haven't sold any shares. I haven't sold any shares. That's correct. Thank you. I'm done. Thank you. That concludes our Q&A session. I will now hand the conference back to Jack Abuhoff for closing remarks. Please go ahead. Thanks, operator. Yeah, to quickly recap, today, we announced yet another highly anticipated win, which we expect to sign tomorrow, completing our eight-week win streak of landing all of the big tech pipeline deals that we presented last quarter as potentially transformative for our company. This, of course, includes two new big tech customers. We believe that these are all companies that are widely expected to forge the path forward in generative AI development over the next several years and to spend billions of dollars of CapEx in, in doing so. You know, we believe these new deals, perhaps individually, but certainly in the aggregate, present a potentially transformative opportunity for our company. As you know, we have a solid track record of land and expand with large tech companies, you know, now with the additional strong tailwinds in generative AI, we think we're extremely well positioned for significant growth in the near and the medium, as well as the long term. We believe we're aligned with an exciting, growing, and dynamic market, that we have the right capabilities and a truly blue-chip client base at this point. I had a question just a few minutes ago about the Bloomberg report, so maybe I'll talk just a little bit about that, you know, it certainly will give you an idea of the magnitude of the opportunity that we've got and the basis for our enthusiasm. You know, Bloomberg released a report stating, and I'll now quote from the report, "The generative AI market is poised to explode." In the report, Bloomberg estimated that the overall market for generative AI-focused IT services, which is what we do, is gonna grow from $83 million in 2022 to $21.7 billion by 2027, and to $85.9 billion by 2032, representing a 100% compounded annual growth rate for the 10-year period from 2022- 2032. According to Bloomberg also, you know, AI-focused IT services are actually among the four hottest market opportunities in generative AI, all with 10-year CAGR of 100% or more. The other three being, generative AI-based drug discovery software, generative AI-based cybersecurity spending, and generative AI driven ad spending. In the same report, Bloomberg estimates that generative AI will become an increasingly essential part of IT spending. In fact, I attended a dinner just last week at which the head of technology innovation for one of the world's largest investment banks, who runs a massive $15 billion IT budget, predicted that 20% of his budget will, within the next few years, be directed toward large language models. It's pretty incredible. My team and I are energized by what we've accomplished, by the magnitude of the opportunities we now have to deliver on our mission, and by the magnitude of the opportunity that's in front of us. Again, thank you all for joining us on our call today. We will look forward to our next call with you. Thank you, everyone. This concludes today's event. You may disconnect at this time, and have a wonderful day. Thank you for your participation.