Good afternoon, ladies and gentlemen, and Welcome To Innodata's Second Quarter 2022 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. It is now my pleasure to turn the floor over to your host, Amy Agress. The floor is yours. 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 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 statement that may predict, forecast, indicate, or imply future results, performance, or achievements. These statements are based on management's current expectations, assumptions, and estimates and are subject to a number of risks and uncertainties, 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 the Ukraine, that contract may be terminated by customers, projected or committed volumes of work may not materialize, 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, whether as a result of the COVID-19 pandemic or otherwise, 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 impairments of the carrying value of goodwill and other acquired intangible assets of companies and businesses that we may 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, cyber attacks, privacy breaches or data breaches that result in the unauthorized disclosure of consumer, customer, employee or customer 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 Form 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. Thank you, Amy. Good afternoon, and thank you for joining our call. Our Q2 revenue was $20 million, representing 17% year-over-year growth. This was slightly below our expectations, due principally to a mutual decision we made with a customer that we believe was beneficial for both the customer and for us. We replaced a one-time medical record AI data annotation project in exchange for a recurring revenue expansion project for our medical record data extraction platform. The original deal included $3.7 million of one-time services and $800,000 per year of ongoing annual revenue. We anticipate that the new deal will increase the recurring revenue component to about $1.8 million per year, extending our services from one to two market segments. The customer's goal is to begin significantly ramping up the recurring work in October after we complete systems configuration. The new deal brings us significantly better long-term value from both a revenue longevity and a margin perspective. It was really a no-brainer for us, but it did reduce Q2 and a little bit of Q3 revenues by approximately $2.3 million. From mid-May through July, several of our largest customers and prospects saw a rapid change in the economic environment and significant volatility in their stock prices. We believe this resulted in a slowdown in new business activity and a few projects being put on hold as these customers and prospects reevaluated their budgets and spending priorities. In the past few weeks, however, we have seen many of these customers and prospects re-embark on their AI initiatives with renewed vigor. We are heartened by the validation this dynamic provided on the critical nature of these AI initiatives, notwithstanding the economic environment. It is indeed encouraging to see signs that the momentum we were experiencing early in the year is returning. That said, with the mid-May through July lull in our customers' activities, together with the change in contract terms I just mentioned, we anticipate that our Q3 revenues will decline somewhat from Q2, probably coming in at about $18 million based on current expectations, but we anticipate Q4 revenue to significantly increase over Q3. Given these Q2, Q3 issues, growth this year is currently expected to be in the range of 15%-20% versus the 30% we have targeted. None of this changes our long-term growth trajectory or our market opportunity. Our confidence stems from the fact that despite what we consider a temporary delay in recognizing revenues from some of our customers, we haven't lost their business by any measure, and we have continued to sign new customers and new contracts. In the second quarter, we added 115 new logos across our segments. This is a 24% increase over the 93 new customers we added on average per quarter in 2021. Indeed, as business activity recovered in the past few weeks, we have either landed or we believe significantly moved the ball down the field on several important business expansions. We signed our fourth SOW and the largest to date with one of the big five American information technology companies, a company we engaged with for the first time 12 months ago. We believe this company spends $hundreds of millions on AI-related initiatives. With a multinational manufacturing conglomerate, one of the largest companies in the world, we just won our first engagement, and we've got a pipeline of 4 other engagements that we're progressing. Just this week, we signed an expanded AI program for content moderation and fraud detection for a leading social commerce marketplace with over 80 million users. Similarly, for another of the big five American information technology companies that we started engaging with a year and a half ago on its AI programs, we're seeing our current $3 million pipeline of new opportunities now moving forward. We're in what I hope will be the final stages of landing a new million-dollar engagement with a new life insurance customer. We're in late-stage discussions with a leading Silicon Valley video game development company that we expect will give us credentials in AI-powered interactive experiences relevant to both gaming and metaverse. Our large social media customer, which as we mentioned in our last call, decreased spend significantly in Q2, has guided us to expect an uptick in monthly revenue from what we were seeing at the end of Q2 and reiterated this expectation of $10 million or more of program spend this year. Our strategy is to become an indispensable partner to companies embracing AI and to serve our customers at their highest point of value. For many companies embracing AI, this means delivering AI lifecycle services and solutions. With our AI lifecycle services and solutions, we provide companies the support they need to collect data, to synthesize data when there is insufficient real-world data, to annotate the data at scale and at high quality, even in complex datasets that require advanced subject matter expertise, and to build, manage, and QA models. Our AI lifecycle capabilities are aligned with the data-centric AI paradigm, which is all about achieving AI performance through data engineering, our specialization. We also have made investments in commercializing our proprietary Golden Gate AI technology stack in the form of an AI data annotation platform, an AI document intelligence platform, and industry solutions that utilize our AI to enable customers to do deeper analytics on textual data and documents with fewer people. We believe that this will enable us to drive shareholder value as a result of multiple expansion as over time, we have greater revenue contribution coming from higher margin SaaS platforms. We're in the early innings of the AI transformation, which is expected to result in 38% CAGR in customer spending from 2022 to 2030. Our strategy is to drive growth via a land and expand strategy, penetrate accounts with significant current or future AI spend, do a great job, and drive revenue expansion with both services and platforms. To execute our strategy, we've made significant investments in sales and marketing as well as product platform development. I'll review our investments by segment. Let's start with Agility. Agility is an AI-enabled software platform for public relations. Agility was recognized for a fifth consecutive quarter as a momentum leader by software review site G2 in its summer 2022 PR software report. Just last month, Business Insider named Agility a fierce competitor against the industry heavyweights that dominate the $5.5 billion PR platforms market. From the beginning of 2021, we invested substantially in Agility sales and marketing. Our investment took the form of increased sales headcount from 14 at the beginning of 2021 to 90 presently. Of this headcount, 42 are quota-carrying. As a return on this investment, we are targeting Agility to grow its annual recurring revenue or ARR by approximately 30% this year. ARR represents the total value of subscription contracts at a point in time. On the product side, we expect to shortly officially launch an exciting Agility product expansion that will enable us to compete in social media analytics, the fastest-growing segment of PR tech. We believe this will be an additional growth accelerator while further expanding our total serviceable market with both existing subscribers and new customer prospects. Now let's shift to our DDS and Synodex segments. In 2022, we expect to have increased sales and marketing spend in these segments by a combined $700,000, and to have invested $8 million in product development. We launched our AI-enabled document intelligence platform in late March as planned. This new customer-facing platform uses our Golden Gate AI technology to automatically extract meaning from complex documents. It can be utilized across domains, from healthcare to financial services to media and entertainment, essentially any business that employs people to read or manage complex documents. Initial feedback from our customers continues to be positive, and we are in late stages with 2 opportunities, and we have several others in pilots and in pipeline. We launched the data annotation platform late last year, which we have continued to iterate and improve. It addresses the data curation, annotation, and introspection challenges, complementing TensorFlow, PyTorch, and GAN AI algorithms. Our platform includes tools to enforce data consistency and learnability, tools to analyze blind spots, bias, and noise, tools to augment data and collect data more efficiently, and tools to select the best data to annotate next in order to maximize system accuracy while minimizing annotation costs. We also launched the initial version of our new banking industry platform on March 31. Our charter customer, one of the world's largest banks, already has 65 people using the product and giving us valuable feedback. The bank's leadership is very excited by how we're able to augment their team's work through our AI-enabled product. The current plan is to bring this product to a wider market next year. Our charter customer has committed to $11 million subscription spend with us over 5 years. In Synodex, our investments are focused on broadening our abilities to serve additional insurance product use cases. We now support 7 product use cases. We anticipate Synodex year-over-year growth to exceed 90% this year. Based upon current assumptions and expectations, we are budgeting to be cash flow positive by the end of Q1 next year as the revenue from these investments ramp up. While the last few months showed us that we're not immune from the macro environment, we believe we're well positioned. AI investments are often justified by business cases that promise lower operating costs and less dependency on hard-to-recruit and hard-to-retain labor. What's more, increasingly, companies are seeing AI investments as necessary to ensure that they're not left behind on what has been predicted to be the next fundamental technology revolution. I'll now turn the call over to Marissa to go over the numbers, and then we'll open the line for questions. Okay. Thank you, Jack. Good afternoon, everyone. Allow me to recap the second quarter 2022 financial results. Revenue for the quarter ended June 30, 2022 was $20 million, up 17% year-over-year. Net loss for the quarter ended June 30, 2022 was $3.8 million or 14 cents per basic and diluted share, compared to a net loss of $0.1 million or zero cents per basic and diluted share in the same period last year. Revenue for the six months ended June 30, 2022 was $41.2 million, up 25% year-over-year. Net loss for the six months ended June 30, 2022 was $6.6 million or 20 cents per basic and diluted share, compared to a net income of $0.3 million or 1 cent per basic and diluted share in the same period last year. Adjusted EBITDA loss was $1.3 million in the second quarter of 2022 compared to adjusted EBITDA of $0.7 million in the same period last year. Adjusted EBITDA loss was $2.3 million for the six months ended June 30, 2022 compared to adjusted EBITDA of $2 million in the same period last year. Lastly, our cash and cash equivalents was $10.5 million at June 30, 2022 and $18.9 million at December 31, 2021. Thank you again, everyone. I'll now turn to John. We are now ready for questions. Thank you. Ladies and gentlemen, the floor is open for questions. If you have any questions or comments, please indicate so by pressing star one on your touchtone phone. Pressing star two will remove you from the queue should your question be answered. Lastly, while posing your question, please pick up your handset if listening on speakerphone to provide optimum sound quality. Please hold while we poll for questions. Once again, that's star one if you have any questions or comments. Okay. The first question is coming from George Sutton with Craig-Hallum. Your line is live. Thank you. Jack, I wondered if you could walk through what you mean by the renewed vigor that you're seeing from some of the clients that had pulled back on their spend or suggested they'd pull back on their spend. Can you give us any specific examples or thought processes as to why that renewed vigor is taking place and what it means for you? Sure, George. Yeah, I named a few of the things that we've closed in the last few weeks and that we significantly moved forward. There are a couple of those that I'm particularly excited about. You know, if you look at the large, you know, US tech companies, each of those is spending, you know, really big dollars on AI initiatives, and it's really important for us to break into those. We think it's a, you know, a land and expand opportunity that is tremendously, you know, potentially lucrative and very, very attractive. We're very glad to see that, you know, in just the last few weeks, we signed our fourth SOW with one of those companies. They're a large, you know, West Coast software company, one of the big five, you know, US companies, with another big five. Similarly, you know, we started with them at a very small level a year and a half ago. Things now seem to be moving forward. We've got a $3 million pipeline that's growing that now seems likely to, you know, pick up pace. You know, Q2 is tough. People stop making decisions. People scale back. People dial down. Now we're seeing that that's, you know, significantly improving. The other thing that's, you know, we're seeing improvement on is, you know, we're continuing to do good work with our large social media company. As we guided in our call last time, their spend was gonna be coming down, as a function of moving to some more developmental efforts. Decision-making around ramping those up seemed to become attenuated, but we're now seeing some, you know, ramp up from the end of Q2 levels, and they're continuing to, you know, guide us to expect that will continue through the year. A lot of the momentum that we're seeing, or when we say we're seeing renewed momentum, it's very much from our pipeline, from our customers, and that moving forward. I guess you also asked, you know, well, why do we think that is? You know, we've been through these kinds of economic things before, you know, in our business, and I've been through it in other businesses. You know, companies oftentimes make pronouncements. You know, we're not hiring new people. We're not signing new deals. We're not making new commitments. Then they use a period of time to, you know, to rank those and prioritize the things that they feel they need to do. I think that it's inevitable that, you know, a business downturn isn't going to fundamentally alter the momentum that companies are evidencing toward moving toward these technologies. I think the technologies are too important. The opportunity that they bring to lower cost, to improve analytics, to improve product is too substantial. I believe what we're seeing is that, you know, after that reallocation process took place, they're moving forward with things that in order to our benefit. Gotcha. One other question, if I could, on the banking platform. The significant size of the first customer is obviously very attractive, and the significant size of that program. When is that going to be GA and something that we could see deployed by other banks as well? It's a great question. Right now, we're very focused on this one customer. We're very focused on them for several reasons. One is, it's gonna be critically important to us to get this right, and they're providing us all sorts of very useful feedback on what they need. They're so big that what they need, you know, what everybody else would need, or most everybody else would need, would be a subset of their needs. So if we get that right, we're well positioned, you know, to GA that for other market participants, number one. Number two, they have other internal groups that are also interested in this, and that would represent internal, you know, expansion opportunities for us, you know, within that bank. In terms of other banks, we're in early discussions with a couple. We're letting them know what we're doing. We're understanding what their you know needs are and how they're thinking about you know these technologies and these capabilities. We'd probably be more formally GA-ing something in the first half of next year, but the discussions are happening now, and there could be opportunities to you know move forward with relationships prior to a formal you know launch. Understand. Thanks for taking the questions. Thank you. Okay. Up next, we have Tim Clarkson with Van Clemens & Co., Inc. Tim, your line's live. Hi, Jack. How are you? Hi, Tim. Good. How are you doing? Good. I was just wondering just on a couple of details. Now, how many salespeople do we have? What you said, do we have 90 people working for Agility, and 42 of them are people with quotas? You know, what I would consider a on the phone-type salesperson. That's correct. You know, we have 90 people in sales in Agility. 42 are quota-carrying. 11 people are, you know, account managers, but they also work to expand accounts. We're doing very well, by the way, in terms of account expansion, which you know, basically tells us that, you know, once we get someone using the platform, they like it, and they want more things from it. You know, for that reason, we're very excited about the launch of the social analytics platform. You know, that's an opportunity to sell more product to our existing customer base. Well, I'm elaborating on your question a bit, but. Yeah. No, that's fine. All right. How many salespeople do we have in the DDS and the artificial intelligence end? In that area, we have nine. Okay. Okay. And then- Now, obviously, you know, the cash is down from, you know, $20 million to about $11 million or so. I mean, is there a backup plan to moderate spend if business doesn't accelerate as much as you expect, or what you're thinking there as far as cash realization is? Yeah. We're targeting that we'll exit first quarter cash flow break even. I think we have a few dials and levers to work in that process. One is that you know we anticipate revenue pickup. Our incremental revenue is very remunerative in terms of contribution margin, incremental contribution margin, so that gives us relief right there. Everything that we're able to enjoy is in terms of these platform developments, a lot of the expensive part of the development is now behind us or will soon be behind us, and we'll be able to start dialing that down. Okay. That's, you know, lever number two. Then, you know, lever number three is a lot of the investment this year was in sales and marketing. You know, everything we learn about sales and marketing, you know, at scale, it's, you know, very much reminiscent of, I guess, what, you know, John Wanamaker's said to have said that, you know, "Half my advertising spend is wasted. The trouble is I don't know which half." You know, marketing is kinda like that. Even sales is kind of like that. You know, because we hit it heavy, we're now in a position to know what works, what doesn't work, what do we double down on, what do we just, you know, eliminate. That gives us a third lever. We'll be working, you know, all of those levers and monitoring it very carefully because I think it's important that, you know, we do so, and I think we have the opportunity to do that. Right. I mean, is there a scenario where, you know, you know, eliminate maybe the bottom 10% or 20% of some of these guys that aren't producing as well? You know, I think that will be part of the way. I mean, it's the way everybody manages companies and especially sales forces. We'll be no different in that regard. You know, I think what we'll be looking for is to use a combination of those levers, you know, revenue growth, product development where the most investment intensive aspects are behind us. And you know, looking at optimizing sales and marketing investments, we'll be managing all of those as a way of achieving our goal. Right. In terms of now, do you think that you're seeing the growth at Agility that you should be seeing based on the amount of salespeople you've hired? The salespeople, you know, need to ramp up. We're seeing better results relative to our internal goals. We've seen better results, much better results than we were expecting in terms of account expansion. We're seeing less than targeted results in terms of no-new logo acquisition, but again, I think that relates back to, you know, not a problem endemic to our sales force as much as a kind of stagflation environment that's causing businesses to, you know, become a bit more conservative. You know, whatever the underlying reasons are, you know, I think we've got the ability to do a good job, you know, mid-course correcting or continuing to, you know, iterate as we move forward. We've got the levers to do that. We've got, you know, the spend that we've got is variabilized, so we're able to do that, you know, pretty quickly. I think, you know, a good result will come from that. Now it looks like the Synodex, the insurance end, that's less affected by the economy. I think everything's affected. You know, our ambitions for that are, you know, for the entire business are pretty significant. You know, we're looking at a very healthy growth rate there, but frankly, we were looking for, you know, much better than that. I think that's been, you know, slowed in the last, you know, quarter or so affected by slow decision-making as well. The good news, especially in Synodex, you see it very clearly, you know, the technologies we've got and the capabilities we have can often be, you know, the business cases that support our programs are ones that hold the promise of lower operating costs and less dependency on people. I think as people you know come around and do their analysis and they you know they prioritize their investments, they'll see this as ranking highly relative to helping them achieve those outcomes. Has the Synodex technology been out there long enough to prove that it's working and it's valuable? I think the answer is yes. You know, I mentioned that there was a shift in, you know, with one of our new customers in terms of them moving from, you know, a feed of data that we were gonna supply them for their own development efforts, away from that and toward a much higher spend, you know, recurring spend on our platforms. One of the reasons that occurred is new management took over, and that new management was coming from one of our, you know, large existing accounts. You know, the managers at the large existing accounts who have grown to trust us and know, you know, how well our platforms work, essentially went over to this new customer that we're working with and said, "You know, what are you doing this for? Let's double down on Synodex platforms." So I think all of that is really good. We've got continued development on our platforms in Synodex. We're not standing still. We're doing a lot of work to more fully integrate AI, and we think that improves our margin opportunity significantly. We also think that it improves our ability to widen our serviceable market for various reasons that are kinda in the weeds. I won't spend a lot of time on them now. A lot of opportunity to improve that and continue to grow that. You mentioned that you added Microsoft as a technology. I don't know what was the exact term for it. You formed a committee on artificial intelligence, and they were the first people to be joining that committee. I mean, is the kind of stuff that Microsoft does, is that different than, say, something that Facebook does or Amazon? Are they all really different or are they relatively similar in terms of the things they're doing? Yeah. I think if we look, you know, across the portfolio of customers we have and use cases, you know, they fall into categories. A lot of people are concerned about, you know, content moderation. People are very interested in robotics, in ad tech, you know, geospatial analysis, chatbot creation. When we look across these, you know, large customers, we've got people who are very focused on document intelligence and robotics. We've got others who are focused on, you know, especially in the social media space, on spam identification, toxicity identification, things like that. The good news is that as we acquire new use cases, you know, we're clearly able to, you know, credibly approach, you know, more and more customers to do things. Lately we're seeing some use cases around anomaly detection in manufacturing. We're seeing use cases around, you know, visual safety. There's a lot of stuff out there. You know, we're very focused on developing referenceability within different use cases so that we can then, you know, take that further and further penetrate the market. Okay. All right. Well, I'm done. Thank you. Thank you. Okay. The next question is coming from Dan Feltz with Feltl Advisors. Your line is live. Hi, Jack. How are you this evening? Hey, Dan. Doing great. Wonderful. I just have like one main question. You guys have made some announcements in the space of synthetic data. Could you talk a little bit about the opportunity and what you think your addressable market will be with that? Yeah. I think it's a very important opportunity. You know, as we've talked about before, you know, AI algorithms are fundamentally trained with data. The problem is sufficient data doesn't always exist. For example, if you're building a anomaly detection algorithm in manufacturing, you need to train that algorithm to recognize defects. The defects, however, may be very rare. They may not exist in large volume. The problem is, well, you know, how do you go about training the algorithms? The answer to that is synthetic data. You can actually create examples of defects that simulate what defects will actually look like. We're now increasingly doing that for, you know, customers for whom we're doing applied AI solutions, who come to us with a business problem like, you know, I want to identify defects in my manufacturing line. We're also doing that for, you know, the large US tech companies who are recognizing that they're, you know, they're building the algorithms, but they need synthetic data in order to get the right performance, by virtue of the fact that either the real-world data doesn't exist in surplus, or they're anticipating that the real-world data starts to shift and morph, and they wanna be able to clearly capture sufficient data from the edge cases in order for the algorithms to perform well. You know, a great opportunity. I don't have a number. I don't know that I've seen any reliable third-party analysts who've put a number on synthetic data, but it is considered universally to be a very important part of an AI program for many of these use cases. Okay, great. Thank you. That does it for me. Okay. The next question is coming from Aria Cole with Cole Capital. Your line's live. Great. Thank you. Appreciate your hosting the call this afternoon. First question is about how you're organized. As you know, in the data annotation industry, companies are able to retrieve data through a large number of crowdsourced freelancers, and you also combine that with in-house full-time employees. I'm just trying to understand better, how is Innodata structured, so that you're trying to leverage the resources you have from people inside and people outside the company? That's a great question. I'll take a step back from that and kind of lead into an answer. Firstly, when we're competing in terms of AI life cycle services, which, you know, includes data collection, curation, data preparation, annotation, one of the ways that we're able to compete very successfully is in terms of data quality. We do better work than most of our competitors, and that work ends up, or the quality of that work directly influences how well the algorithms perform. How do we do that? You know, the answer is that we've been in the data business for many now decades. We've been serving up the highest quality data to large information providers, for now two decades, and we've gotten very, very good at that. Part of what makes us good is our DNA, part of what makes us good is our technology and how we manage data projects. I think that experience has given us the ability to rely primarily on, you know, internal people who are managed very, very carefully, but it also has given us the flexibility to use people on a freelance basis where that's appropriate for projects. We're not a crowdsourcing company. You know, we find that we're able to compete effectively against crowdsourcing companies because we have everything that I just mentioned. All right. To follow up on that question, you know, the Big Five US technology companies and others, you know, they're bringing on clients like yourself and call it 50 other data annotation companies. How are they going about trying to determine which of these data providers like you are the best ones that they can depend on the most? You know, as you realize, you're getting into these companies, but it's all about, you know, a data quality war, so to speak. You need to show that you're better than the other people who brag they're really good. How do you go about proving to these sophisticated customers that you, in fact, deserve to be, you know, among their, you know, their go-to or their primary customers versus others who are not data providers of the same quality? Yeah. We certainly don't run into 50 competitors. We regularly run into three or four. What we try to do in any competitive situation is, as quickly as possible, get to some proof of concept. As quickly as possible, get to work. Because we'd rather let our work speak for ourselves than have salespeople and marketing literature speaking for us. What we find is as soon as we can get in. That's why we consider it a land and expand opportunity. As soon as we can get our foot in the door, and as soon as we can get to a POC, we begin to distinguish ourselves. As we distinguish ourselves, one SOW leads to two more, and that leads to three more, and things progress from there. I think there's a very significant opportunity to you know build POCs, to begin doing that work, to distinguish ourselves and then to expand, and claim an increasingly large portion of share of wallet with a lot of these large customers. Okay. One last question about this subject. Let's assume that your data quality is excellent, and that's why you're gonna be winning new business with customers going forward. As you scale up and the company potentially doubles or triples in size, how are you going to be able to maintain the quality of work you do today? Because as you know, obviously, going from, you know, 200 employees to 600 employees doing this work is not easy, especially if you're trying to hire quickly. Yeah, that's absolutely true. You know, I think what I would say is, you know, I'd go back to, you know, who we are. You know, we've been annotating data for a different use case. We've been annotating data at scale for companies who are intolerant of error for two decades. We've scaled up, you know, and sometimes we've had to scale down. In fact, you know, if you look at our performance over many years, you would see growth around very large projects where we had to scale up and we had to scale down. Now, the problem that we had was that our market wasn't very large. Every now and then, there would be a large project, and we'd rally around it. In scaling up and scaling down, for us, that was a little bit like going to the gym. It was exercise. It was leading up to the moment we're in today. We built the sinew and the muscle to be able to do that. We built the underlying technologies in order to be able to do that. Now as we approach this vastly more dynamic and larger market and fast-growing market, we're able to bring those capabilities to bear. I think those are distinguishing us from among the, you know, the three or four competitors that we're lining up against now on a more regular basis. All right. Well, listen, thank you very much and best of luck. Thank you so much. I'd now like to turn the floor back to Jack for any closing remarks. Thank you, operator. So, you know, as we discussed today, our I guess I'd call it a mid-year lull is the result of a deal renegotiation that is actually very good for us. You know, a Q2 in which pace of customer decision-making, you know, absolutely slowed. Customers just weren't committing, even though we were piloting more and more potential engagements. Now, the good news is that in the past few weeks, things are moving again. Two companies that are moving again are among the top five largest American tech firms, big spenders on AI and both relatively new relationships for us. Even though we're contending now with a mid-year lull, we're clearly regaining the momentum from earlier in the year, and we anticipate closing the year with a strong head of steam. Thank you all for joining us today. I will look forward to our next call and otherwise sharing with you our progress. Thank you, ladies and gentlemen. This does conclude today's conference call. You may disconnect your phone lines at this time and have a wonderful day. Thank you for your participation.