Good day, and welcome to the Innodata Q4 and fiscal year 2021 earnings call. Today's conference is being recorded. At this time, I would like to turn the conference over to Amy Agress. Please go ahead. Thank you, Kevin. Good morning, everyone. Thank you for joining us today. Our speakers today are Jack Abuhoff, CEO of Innodata, and Marissa Espineli, VP Finance and Corporate Controller. 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 fourth quarter and the twelve months ended December 31, 2021. 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 COVID-19 pandemic and the responses of governments, the general global population, our clients, and the company thereto. Impacts resulting from the rapidly evolving conflict between Russia and the Ukraine, that contracts may be terminated by clients, 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 clients to reduce, delay, or cancel projects, the likelihood of continued development of the market, particularly new and emerging markets that our services and solutions support, continuing Digital Data Solutions segment revenue concentration in a limited number of clients. 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 clients and prospective clients 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 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, client, employee, or company information or service interruptions. Various other competitive and technological factors, and other risks and uncertainties indicated from time to time in our filings with the Securities and Exchange Commission, including our most recent reports on Forms 10-K, 10-Q, and 8-K and any amendments thereto. We undertake no obligation to update forward-looking information or to announce revisions to any forward-looking statements, except as required by the federal securities laws, and actual results could differ materially from our current expectations. Thank you. I will now turn the call over to Jack. Thank you, Amy. Good morning, and thank you for joining our call. Today, we're very pleased to announce fourth quarter revenue growth of 26%, a strong finish to a transformational year in which we have seen increasing momentum from new customer wins and significant customer expansions. In 2021, overall, we grew 20% revenue. In 2022, we are targeting an acceleration of revenue growth to 30%. Achieving this goal is subject to various risks and uncertainties that we refer you to our filings with the SEC. That said, we believe we are seeing solid business momentum and traction across our markets, including financial services, manufacturing, retail, robotics, and technology. I'll share with you some examples of traction we're experiencing with some of the largest Silicon Valley tech companies. As you may recall, last March, we announced an expansion of business with a leading social media platform. Since that time, we have further broadened and extended our relationship with the social media platform. We're cautiously optimistic that revenue from this company could approach $10 million-$15 million in 2022. Here's a recent very important win. One of the largest Fortune 50 semiconductor manufacturers selected us to build fully trained deep learning AI models for automated retail and manufacturing solutions. This is an example of end-to-end AI services from synthetic data creation to model training and model management. Last September 2021, we signed our first deal with one of the world's top five tech companies, a leading software company. I did not wanna make too much of this until we got some traction under us, but now that's happened. We've now expanded to support multiple of their core engineering teams in developing AI document classifiers. We're also seeing significant expansion in another top five tech company that we began providing AI data annotation services to in the second half of last year. Today, we are providing this company data annotation services for content moderation, intelligent document understanding, and computer vision. We believe that this relationship will continue to grow in 2022. We're also providing synthetic data services to two of the world's largest robotic process automation companies. With another top social media company, we signed an enterprise subscription for our media intelligence platforms and solutions. Lastly, Google has authorized Innodata as a build and services partner within its Partner Advantage program. We've been asked to specifically focus on Google's 5G edge computing initiatives to help Google's customers accelerate end-to-end AI software and solution development powered by Google Cloud's Vertex AI products. Based on data received from market conversations with customer prospects, we estimate that three of the companies I just mentioned spend in the aggregate approximately $2 billion annually on AI enablement services, solutions, and platforms of the type that we now provide or intend to be providing later this year. The market traction we have been experiencing, combined with our estimates of the spending capabilities of companies we're now engaged with, and industry overall growth projections, has given us the confidence to budget increased investment in both sales and marketing, as well as new product creation. In 2021, we invested $14.5 million in sales and marketing and new product creation. In 2022, we are budgeting an increase in that investment to approximately $27.5 million. In our DBS and Synodex businesses combined, we expanded from seven quota-bearing sales executives to 11 in 2021, and we expect to exit 2022 with 18 sales executives by mid-year. In addition to this, late in the second half of the year, we expect to bring on approximately 10 additional quota-bearing sales executives who will be selling our new DBS platform products in 2023. In our Agility business, we expanded from 14 quota-bearing sales executives and account managers to 59 in 2021. In 2022, our expectation is to expand the Agility sales team only marginally to 66 quota-bearing sales executives. In Agility, we also brought on 34 sales managers and business development reps in 2021. I'll talk a bit how we think about these investments and being good stewards of shareholder capital. First, let's address investments in sales and marketing. We target long-term value of new wins to be 3-5 times our customer acquisition costs, which we think is achievable because our solutions and platforms tend to yield high levels of recurring revenue and significant lifetime customer value. In the fourth quarter, we categorized 92% of our revenue as recurring. We target only profitable growth from strategic wins, and we enjoy the benefits of strong operating leverage on fixed costs from incremental revenue. On the product development side, our discipline comes from developing solutions that address real-world problems. We even charter customers into the development process from the start and carefully validating market opportunity. We are launching 6 new platforms in 2022 that we expect will be major contributors to our growth in 2023 and beyond. While these significant investments will result in the use of some of our cash in 2022, our cash burn is expected to peak in the first quarter of 2022 and decline as our revenue grows in the subsequent quarters. Based upon current expectations, we are budgeting to be cash flow positive by the end of 2022, with significant increases in cash flow expected thereafter. With $19 million of cash and no debt, we expect to fund these investments from our internal resources. In 2022, we anticipate growth will result from a combination of new customer wins and customer expansions across our segments. Indeed, with most of the large new customers we brought in in 2021, we see opportunity to expand the relationships into multiple buying centers. Leveraging trends in 2021, we are budgeting a 30% increase in year-over-year revenues in 2022, an acceleration from the 20% growth we achieved in 2021. Longer term, our business plan calls for approximately $200 million in revenue and approximately 30% EBITDA margins by 2025. This business plan calls for us to complement today's service offerings with new managed service offerings and new platform-based offerings that we believe businesses will find useful to adopt and manage AI. In addition, our plan calls for us to develop additional SaaS platform products that encapsulate our proprietary AI in order to reimagine legacy, slow, and inefficient knowledge-based processes. Of course, we are laser-focused on execution to ensure that we capitalize on the opportunities in our industry and position the company to be ahead of the curve in terms of our customer needs. In 2021, we accomplished key steps to re-architecting our business for growth. We built a world-class enterprise SaaS product engineering capability. We also built a robust enterprise software sales and marketing engine. We embraced remote working, both culturally and technologically. As a result, we removed geographical boundaries, variabilized our resource spend, and made our business less fixed cost and capital intensive. In my remarks last quarter, I likened our business to a flywheel that starts with a bunch of small turns, but gains momentum and speed as it builds on itself and produces more and more positive results. With Q4 representing our sixth straight quarter of year-over-year growth, we believe the flywheel indeed appears to be gaining speed. If we look out over the long term, our vision is that Innodata is seen by the markets as an essential player in the dynamic AI ecosystem, and it's seen by its shareholders as an exciting growth company that outperforms expectations. Late last year, our board concluded that our growth and momentum required the support of a full-time CFO. In December, we engaged a leading recruiter to execute a retained search. The search has progressed well, and we expect to announce a new full-time CFO over the next several months. Mark Spelker, who served as our part-time CFO, has resigned from the position effective this week. We have appointed Marissa Espineli, our Vice President of Finance and Corporate Controller, as our interim CFO. Marissa, a certified public accountant, has a successful 20-year track record with us and has been spearheading our global finance organization, including operations, tax, internal control, planning and forecasting, financial reporting, and in the last 3 years, SEC filings. I'd like to take this opportunity to welcome Marissa to today's call. I'll now turn the call over to Marissa, who will quickly take you through our numbers. Thank you, Jack, for welcoming me on this call. Good morning, everyone. Allow me to share our results for the fourth quarter and fiscal year 2021. Revenue for the quarter ended December 31, 2021 was $19.3 million, up 26% year-over-year. Net loss for the quarter ended December 31, 2021 was $1.2 million or $0.04 per basic and diluted share, compared to a net income of $1.2 million or $0.05 cents per basic share and $0.04 cents per diluted share in the same period last year. Revenue for the year ended December 31, 2021 was $69.8 million, up 20% from $58.2 million in 2020. Net loss for the year ended December 31, 2021 was $1.7 million or $0.06 per basic and diluted share, compared to a net income of $0.6 million or $0.03 per basic share and $0.02 per diluted share in 2020. We are ending our year-end with cash and cash equivalents of $18.9 million, compared to $17.6 million in December 31, 2020. Again, thank you everyone. Operator, we are ready for questions. Thank you. Ladies and gentlemen, if you'd like to ask a question, please signal by pressing star one on your telephone keypad. Please ensure that the mute function of your telephone is switched off to allow your signal to reach our equipment. Again, please press star one to ask a question. We'll just take a brief pause to allow all participants the opportunity to signal for questions. Our first question today comes from Marco Petroni of MG Capital Management. Hey, Jack, how are you? Great quarter. Just like to ask a little bit about the Google relationship and if you can go into a little bit of that and what that potentially can mean for the company? Thank you. Sure, Marco. It's early days with that relationship. We're very, very excited about it. If you want a kind of a fuller, more technical description, you can click on the link in our press release and go to Google's partner page, and it explains what we're gonna be working with them on. Basically, it enables us to work closely with their sales force and to become engaged working with their customers on 5G and Edge-related AI solutions. V ery excited about that. I think we look at that as one of the growth seeds, one of the important growth seeds that we've planted. Very happy with where we are with it now. W e think that the future with that partnership is very exciting. Okay. Thank you. Thank you. Our next question comes from Tim Clarkson of Van Clemens. Hey, Jack. Great quarter. Just some background on some of the stuff going on. I know that you mentioned that you're expanding this relationship with a leading social media company. I'm guessing it's Facebook. I know you can't say. What is the value that they're getting from this? I mean, why are they doing business with Innodata and not somebody else? Yeah, no, it's a great question. I think that we've got some competitive advantages in the market that I think are clearly inuring to our benefits. First is that as you know, better than many, we've got a long legacy in the creation of very high quality, consistently high quality data. When you're building AI algorithms, there's really nothing more important than training those algorithms with high quality data. That is and has been a distinguishing capability that we have when we go to the market with many companies who are critically concerned that their AI performs well. So we've got that. The other thing that we've got going for us that is distinguishing us in the competitive landscape is our full service AI capabilities. We're able to demonstrate to them technologies that make the process of creating high-quality data more effective and efficient. We're able to show them our platforms. We're able to get them involved as a charter customer in the kinds of things we're developing that are platforms that we would hope that they might be licensing from us someday soon. You know, a lot of great capabilities, but it really starts with the embracing the basic fact that, you know, unlike traditional applications that are built with Java and Python code, primarily, AI is primarily built with clean, synthesized or, you know, real-world data that is prepared in a scrupulous way in order to train the algorithms to perform well. Right. Sounds easy to do, but it's not. No, it doesn't even sound easy to me because I know it's not. Okay. Yeah. It's complex, but it's something that we've been training to be good at for many years. You know, the kinds of companies that, you know, the bar was always high. The work that we've done over the years for, you know, the largest information providers, the most demanding companies in the world who couldn't tolerate error, prepared us for today, and now we're up for the challenge. Right. We're ready for it. Yep. Right. Now, you mentioned last quarter that you were hopeful that you're gonna have a particularly good quarter in Synodex on the insurance business. Does that still look good? The business still looks very good. We had a little bit of a hiccup in terms of getting some of our technologies rolled out, but you know, we think we're overcoming that. The business is still there. The bookings are still there, and the contracted business is still, you know, very large. You know, I'm actually very, very bullish on that business for 2022. The technology challenges in terms of you know, and a lot of what we're doing there is we're harnessing AI in new and creative ways. You know, as we do that, you know, it, the things that we're doing even throw off new product opportunities and new and innovative exciting things that we can be doing as we're learning so much. You know, very bullish about that business. I think the prospect of being able to harness AI to extract medical data is transformative and I think we're gonna see great growth from it this year. Sure. Now you hired a ton of people on the Agility segment last year, and are you still looking at once these people are up to speed at about 500,000 or so per salesperson? Is that still a believable number? Yeah. The quota is less than that for this product. It's closer to about $4.4 million per year. Okay. as a quota. I think the important thing, you know, we dramatically expanded it. We built a lot of the infrastructure in terms of sales management, sales enablement, sales training, and you know, BDR capabilities in advance of bringing on the quota-bearing sales executives who depend on those functions to be successful. You have to do it that way. Right. Right. We brought them on late in the year. You know, when you bring them on, it's like a two-month training process. Then there's ramp up and pipeline development and all of those good things. You know, I believe clearly that we're going to be seeing substantial revenue contributions from them in 2022, as they move up that productivity curve, meaning that they're not producing their full, you know, monthly allocation of quota immediately. Right. Producing a percentage of that. When you roll that in, you know, that starts to be accretive in terms of revenue, and then in 2023 it gets even better. Right. Now in terms of adding people on the AI and salespeople, how many people are we looking to do there? We ended the year with about eight on the pure AI side, with three new people on the Synodex side, which is, you know, becoming an AI play really. We're estimating to end the year with about 24 on the DBS AI side and probably four on the Synodex side. Okay. Um. Their quotas are higher than? Their quotas are higher, but again, there's a ramp-up curve. You know, people have to build a pipeline and such. And then the other thing I'd say is a portion of those people are coming in in the first half of the year, and they'll be selling, you know, the AI managed services and the capabilities that we, you know, are primarily selling today. And then a portion of those people, about 10 of them, will come in late in the year, and they'll be executing product sales. You know, selling our new platforms, primarily, contributing to growth then in 2023. Right. Yeah, I guess, you know, the other question I had, you had a number on what you're gonna spend on both salespeople and on product development. Can you split that out? How much of that new spend is gonna be product development? How much is gonna be sales and marketing? Yeah. In terms of 2022, you can think of about, you know, in rough terms, we'll be expensing about $17 million. That'll be, you know, our sales force and our marketing capabilities. You can think of about $7.5 million is, you know, capitalized software development costs. Okay. So far I know that, you know, your core competency is in the accurate data. Have you developed additional AI products that are actually selling and creating value beyond just the accurate data annotation? Yeah, no, we are. We've got a lot of things in the works. You know, we'll be bringing to market. I think of it as 6 new platforms. One of them was actually launched, you know, like November, December last year, but you can effectively think of them as six new platform products, all of which are AI enabled by our GoldenGate platform, this year. Part of what we're doing is we're creating industry solutions. You know, looking at the kinds of work people do and the way they did their work pre-AI, and we're saying, "Well, you know, how can we reconceptualize this in a world that is now capable of tapping into these technologies?" Part of it is taking the work that we do in DDS as a managed service and creating customer-facing tools that people can use to do things with AI themselves, which include, you know, data training and preparation. Also includes model management and deployment around activities that relate to document analytics and document processing. Is it easy to demonstrate the return on investment on products like that? It's a good question. It will be easy to demonstrate returns on investment for the AI management deployment and document processing solutions because we've done this with customers. We've demonstrated the technology. We show them that it works. Then you go and you know, you model what their resource consumption is in today's state, and then you model a resource consumption in a future state, you know, augmented by AI. You know, the results of that are pretty compelling. I mean, you're looking at like 30%-50% savings, and then those savings become greater and greater as your algorithms become more and more trained. Okay. The cool thing is we're able to start them out with high performance because of the way we've built our AI technologies. You know, there's a lot of transfer learning, it's called. They work quickly, immediately on new tasks, but then as they become trained on those specific customer-specific tasks, they contribute more and more, you know, value as that goes forward. Right. One last question. I know that you're always on the lookout for what, you know, other companies similar to you are valued at. What, what's your sense of what the valuations are out there for companies like Innodata would be on a price to sales basis? We're seeing some very high valuations. You know, I'm confident that if we execute our plan, we will obtain those valuations or better valuations ourselves. You know, I think if we were a private company with like one or two of the clients that we now are dramatically ramping up business with, we'd be valued at some exorbitant number. You know, I don't worry about that. I focus on execution. I think that if we execute the plan that is on my desk, the stock price is gonna take care of itself. Right. One last question. This is just kind of a curiosity. I mean, in terms of where you thought the company was, say, three years ago and where it is today, I mean, what are the biggest positive surprises that you've seen? I mean, there are so many of them. I think we'd need a longer call, and if I start listing them all, we'd lose, you know, whomever may be listening right now. I think there are things that we look at anecdotally that we take a lot of pleasure in, and then there are things that are, you know, transformative, where if you take a step back, you realize, you know, how much change has taken place. You know, for many years, decades, we suffered with the fact that there were only, you know, four large companies who cared about quality data, and that was our market. Now, our market is any company that is looking to embrace AI, because AI is trained with data, so you have to start there. You know, as we began to appreciate the breadth and the size of the market and the diversity of use cases, we began to, you know, assemble and develop competency in many more of these use cases. We're supporting like 50 different use cases right now in AI. That is just really cool and exciting. So, you know, from a day-to-day basis, what you see is new pipeline and new relationships being formed, you know, on a regular and ongoing basis. You know, all of that's very exciting. From an anecdotal perspective, you know, I can just like think in the last few weeks, you know, the things that get me very excited. The Google partnership is one of them. Another one is one of our very large, you know, banking clients said that their CEO is interested in the work that we're doing and may want a demo of what we've developed. You know, that is just super cool. Innodata is creating technologies that the CEO of one of the world's largest bank is not just talking about, but wants to come to a meeting and look at. There's a lot. I could go on, but. Sure. Cool. Thank you. Well, I've been hogging the call, so I'll open it up to other people. Thank you. As a reminder, ladies and gentlemen, please press star one to ask a question. Our next question comes from Dana Buska of Feltl. Hi, Jack. Hey, Dana. Good morning. Hi. Congratulations on a wonderful quarter. Thank you so much. You're very welcome. My first question is that you recently hired somebody to head up your applied AI. Could you talk a little bit about what your ambitions are for your applied AI group? Yes. What we're looking at is two things. We're looking at ways that we can help companies who have knowledge-intensive processes, you know, document-intensive processes, harness our AI to achieve better outcomes and greater efficiencies, you know, in those processes. And that's what he and his group were looking at. The derivative benefit of those engagements is you start to see commonality among engagements. You start to see, you know, processes that are susceptible to, you know, new industry solutions. We see that group as both contributing, you know, revenue over time and being kind of a you know, out there to help us from a potential product development perspective, identify new opportunities to build solutions. You know, this year, I'm very happy with the progress we've made in developing under Steven Davis an enterprise software capability that we've never had before. W hat Steve is looking at is. What Rahul, you know, on the product management side is looking at is obtaining new ideas from these kinds of engagements. Learning new processes, getting deep inside some new industry that does a specific thing and are looking to do it better. Then you know, take a step back and you say, "Well, who else, you know, does this? And who else needs to do it?" What we, you know, we anticipate discovering is that these things will not be, you know, unique. They'll be generalized in their applicability, and that will give rise to the opportunity to develop new industry solutions. Okay. Great. It's kinda like a consulting group. Is that kinda how you're thinking about it then? You can think of it as a consulting group. You can think of it as a sales group. You know, they're gonna carry quota. They're gonna, you know. They're not just there to, you know, call them. You know, they're out there, shaking the trees for opportunity. Okay. Excellent. I had read recently about Innodata data annotation, and they were talking about data annotation becoming a new programming. Is that something that you're seeing? Could you talk a little bit about that, how annotated data is becoming like programming? Yeah. Traditional applications were built with computer code, with many lines of code. You know, the problem with them was that they were very expensive to maintain. They were difficult to manage. They were expensive to build. AI works differently. AI, there's programming involved, but most of the work that's involved to, I'll use the term, you know, generically, to program them, is training using paired data sets of input and output. Sometimes people use the word annotation, sometimes they use the word labeling. It applies to, you know, all types of data, from image data to video data to textual data to audio data. The problem set is, well, how do you build instances of input and output relative to a data? How do you label data at scale with high levels of accuracy so that your models work well? That's exactly, you know, the thing that we've been working on now for, you know, many years and that we've gotten very good at. Well, it sounds like an exciting time for you. One last question. You're talking, reading the numbers here, 30% revenue growth for this year, and it looks like to hit your target for 2025, that would be a 30% compounded revenue growth. Am I figuring that right? Yes, that's right. Okay. Could that be too aggressive? It might be. You know, I think our intention is to be aggressive. You know, our intention is to invest substantially. We think that there's a very large market opportunity in front of us. You know, the plan right now calls for using internal, you know, resources in order to make those investments. We made money on things that we've done in the past. We've made money on our Apple e-book program and other large programs that we've had, and we've kind of waited for the right opportunities to deploy those funds and to put them to work for you know the business. I think we're now at the time when doing that is exactly the right thing to do. Wonderful. That just sounds excellent. Again, congratulations on a wonderful quarter. Thank you so much. If there are no further questions, I'd like to put the call back to Jack Abuhoff for any additional or closing remarks. Great. Thank you, operator. I guess to quickly recap, we're optimistic about our ability to penetrate a very substantial opportunity over the long term as a result of the market traction and the customer expansion that we've been seeing. As a result, in 2022, we anticipate continuing to expand our sales and marketing as well as new product development. We're expecting that our dialed up investments will result in use of cash in 2022, but our strong balance sheet allows us to fund these investments, like Dane and I were just saying, from internal resources. We hope to reap the benefits of these investments in 2023 and beyond. We've delivered accelerated 26% revenue growth in Q4 and 20% revenue growth in 2021 overall. We're targeting to deliver 30% revenue growth in 2022. Longer term, our business plan is aggressive, but we're budgeting approximately $200 million in revenue and approximately 30% EBITDA margins by 2025. I think later today we'll also be posting a new investor deck on the investor section of our website. I just want to throw that out there. It'll, you know, have a little bit more detail and I hope be helpful to everybody. Again, thank you so much for joining us today. I will be looking forward to our next time together, which will come pretty soon, for our Q1 call, excuse me. Thank you very much. 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