Good morning, and welcome to the Innodata Fourth Quarter and the Year Ended December 31, 2019 Earnings Call. Today's conference is being recorded. At this time, I would like to turn the conference over to Ms. Amy Agress. Please, go ahead, ma'am.

Thank you, Anne. Good morning, everyone. Thank you for joining us today. Our speakers today are Jack Abuhoff, Chairman and CEO of Innodata; and Robert O'Connor, our CFO. We'll hear from Jack first, who will provide perspective about the business, and then Robert will follow with a review of our results for the fourth quarter and the year ended December 31, 2019. 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 the Section 21E Securities and 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 our management's current expectations, assumptions and estimates and are subject to a number of risks and uncertainties, including, without limitations, that contracts may be terminated by clients, projected or committed volumes of work may not materialize in whole or in part; the primarily at-will nature of contracts with our Digital Data Solutions clients and the ability of these clients to reduce, delay or cancel projects; the likelihood of continued development of the markets, particularly new and emerging markets that our services support; continuing Digital Data Solutions segment revenue concentration in a limited number of clients; our inability to replace projects that are completed, canceled or reduced; our dependency on third-party content providers in our Agility segment; depressed market conditions; changes in external market factors; the ability and willingness of our clients and prospective clients to execute business plans, which gives rise to requirements for our services; 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 acquire; changes in our business or growth strategy; the emergence of new or growing competitors; potential effects on our results of operations from interruptions in or breaches of our information technology systems and various other competitive and technological factors; and the 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 morning everybody. We're pleased to be reporting a Q4 with the sequentially increased revenue and gross margins. We're looking to make 2020 a growth year. And 2019 was the year we've laid the necessary groundwork for that. Most important thing we did was to design and launch a set of solutions and platforms that we believe will enable us to address the market for AI and machine learning data preparation solutions. This is a significantly larger market than our traditional markets and a market that is forecasted to grow rapidly in the next few years. The market for AI and machine learning data preparation solutions is estimated at $1.5 billion in 2019 at the end of last year and to grow to $3.5 billion by the end of 2024. The reason it's expected to grow by this much, is that it proxies the growth in AI solutions overall, which is expected to have a CAGR of 35% over the next few years and reach $53 billion by 2026. The reason that overall AI solutions market is a proxy for the AI data preparation solutions market is because the most important ingredient to a successful AI solution is proving to be the quality and quantity of data that is used to train the system. In fact, the performance of AI systems is directly proportional to the training data volume and quality. That is forcing data scientists that companies embarking upon AI solutions to spend 80% of their time on data preparation tasks, which is a big problem as they lack the technology and the resources to deal with the amount of data preparation required. We believe that everything we have been and everything we possess from our culture to our technology gives us a competitive advantage as…

Thank you, Jack. Good morning everyone. As Jack said, we've begun validating our redesign solutions with new customer wins and a growing pipeline, and we look forward to sharing with you in our next call, the metrics related to our growth in new markets. Before I get to the year-over-year numbers, I would like to share some fourth quarter highlights. Revenue increased by approximately $800,000 over the third quarter of 2019 and gross margins improved quarter-to-quarter from 35% to 38% as a result of higher revenues. Our adjusted EBITDA was $1.5 million in the fourth quarter compared to $914,000 in the third quarter. After deducting tax expenses and minority interest, our net income in the fourth quarter was $58,000 compared to a net loss of $556,000 in the third quarter of 2019. Our cash and investment balances were $10.9 million in the fourth quarter, approximately $2 million point [ph] lower than the third quarter. The decrease was mainly due to our share repurchases of 1.8 million made during the quarter. On a year-over-year basis total revenue for the year ended December 31, 2019 was $55.9 million, a decline of 3% from $57.4 million in 2018. Net loss was $1.6 million or $0.06 per basic and diluted share for the 12-month ended December 31, 2019 compared to a net loss of $300,000 or $0.01 per basic and diluted share in 2018. Adjusted EBITDA for the year ended December 31, 2019 was $3.3 million compared to $6.4 million for the year ended December 31, 2018. Cash and cash equivalents were $10.9 million at both December 31, 2019 and December 31, 2018. Thank you, operator. We'll be ready for questions now.

Yes, sir. Thank you. [Operator Instructions] And we'll take our first question from Tim Clarkson with Van Clemens.

Hi guys. Hi, Jack.

Hi, Tim. Good morning.

Good morning. Can you just explain this – all this artificial intelligence stuff is new to me and I'm sure it's new to most people and why don't we focus first on this annotation business. Can you explain what it is and can you explain how big the market is and explain why you think Innodata can really excel and beat the competition in it?

Sure. So in terms of market size, Tim, we're seeing that the data preparation market is growing very substantially estimated at about $1.5 billion at the very end of 2019 and that's expected to go to $3.5 billion by the end of 2024. So that's clearly an aggressive growth rate. And what's funny is there are other statistics that I've come across that are even more bullish than that when I've chosen to quote a more conservative one. So the thing about AI systems, which are clearly becoming the rage is that they require training data in order to learn. They learn patterns and they learn to recognize things and to categorize things. But what they require is input in order to prime the pump, input in order to have data that's labeled in order to then generate the learning that takes place through the neural networks. So one, early adopter of this technology has been autonomous driving and in order to create autonomous driving AI systems, it required lots of people sitting in front of computers who were drawing bounding boxes around things like stop signs on visual images. So people captured a lot of imagery and then they needed people to sit and say, this is a stop sign and this is a double yellow line, and this is a lane marker, and this is like the cow in the middle of the road. Now as the technology begins to move more mainstream and use cases are being discovered that go well beyond that, the complexity of the annotation task becomes more complex as well. What's still required is training data and the quality that one gets from the systems is still directly proportional to the amount of data and its quality. As the subject matters become more complex, so instead of drawing bounding boxes around stop signs, you’re deciphering meaning in complex banking documents for example. Then you need people with different levels of skills and, but that's what we bring to the table. We bring the people, the domain expertise and financial services and law in healthcare to name a few. And we bring the technology that we've been working on and investing heavily in the last three years that helps us create a very, very high quality training data at large scale efficiently that people can then use to train these AI systems. Was that helpful?

Right. And how does – how are you guys doing against the competition in this market?

So, I want to emphasize that we're – it's still early days for us. We're kind of – we did a lot of preparatory work last year to have very compelling offerings that we would go into the market with. But based on what we've seen last quarter and what we're seeing so far in first quarter is we bring very substantial competitive advantage to the market. We're able to produce higher quality data than the leading companies in the data annotation sphere, when it comes to complex data. Now, it's very simple, drawing bounding boxes around stop signs, that's probably not our addressable market. That's not where we bring as much relative competitive advantage as we do and it becomes more complex. Now the cool thing is, and the thing that excites me a whole lot is that the work that we've done historically for large information publishers is of the highest complexity out there. And that's what we've sharpened our tools with. That's what we've trained our AI for. So now as we move into some of these other areas, there are new competitors find to be very challenging. For us it’s actually, in a relatively not as difficult as other things we've done. So we think we're incredibly well prepared and we're just really jazzed about this new market that we've discovered

Right. Now, how does this market compare to your legacy market size-wise?

There are no reliable third-party statistics on the legacy market. But we estimate it to be about $250 million in size and we're referring to now as our core data solutions area.

Right.

When you add up the revenue of our direct competitors, the larger ones and some of the fragmented ones and do a little bit more math around that, it's about $250 million. So when we look at a market that is presently $1.5 billion expected to grow to $3.5 billion that's a much larger market. The other factor is that the existing markets are probably not growing, if anything they're starting to shrink and there are a lot of reasons for that. Mostly that the information services market itself, the publishing market is at best single-digit growth.

Right.

So between price compression and a lot of other things that it's not a growth market and it's constrained market. So what we're trying to do is we're not giving up on that market by any measure. We're still very interested in it. We've got a leadership position in it. We're going to keep, and we're going to maintain that. We're going to take good care of our customers, but at the same time we're pivoting to this much larger growing opportunity, which we're finding it very exciting.

Right, right. Now, I noticed today in today's Minneapolis start reviewing that Wolters Kluwer – just making a major expansion in the AI area and the legal area. Is that something that you were involved in or can't you comment on that or what's – I know that Wolters Kluwer is a good client of yours?

So yes, Tim. As you know, we never comment on individual clients and their strategies and what we're doing with them. They are a major information provider. We're working with leading information providers, applying AI to content operations on their behalf. And we're receiving very good market recognition in those markets for having done that. There's a lot of excitement about what we're doing. But I do think the real story here is that we've – through that effort we’ve – and most notably the investments we've made over the past three years in AI being applied to those kinds of challenges, we're now very well positioned to pivot to these larger markets or to, I should say embrace these larger markets.

Right, right. I know that there's another niche that's a little more complicated, I don't exactly fully understand and that's where you're using proprietary machine learning to enable you guys to analyze, for example, financial deals and be able to come with analysis in maybe a half an hour, an hour, which might take legal experts two or three or four days to get to the same point.

Well, a lot of this starts to either relate to each other depending upon the projects. So there are a lot of people, for example, with lots of intelligence or knowledge that’s bounded up in documents, financial services documents for example, healthcare documents. And what we're working on is being able to unlock that intelligence and put that into systems that enable them to do analytics around that. So for example, we just closed a deal and this is just a couple of weeks old with a very major, very significant hedge fund where we're doing exactly that. We're taking documents that they've got. We're unlocking intelligence that resides within the documents. And we are servicing them with our new data analytics platform, which they're using to do a better job, managing that documentation.

All right. Now in terms of the aspiration, what's a realistic percentage of Innodata’s revenues by end of the year that could be directly tied to new AI ventures?

It's a little hard to say, I think what we're doing is, we’re very focused on the wins that are directly in front of us. Our goal is to double the amount of business that we book in our core business this year and to make the wins very referenceable, very notable and kind of wins that will be recognized broadly in the markets. I think if we can do that, then we start to get the division growing. The other thing that we're going to be doing is we're going to continue to be emphasizing the platform strategy. And as you know, we've planted flags there with Agility and Synodex in the past. We're also creating the data analytics platform that I referred to as well as a new data annotation platform that we're bringing to market. And the cool thing about those markets is, there's not – there's so much repeatability and such a high-level of retention hopefully, that you end up being where we're finding ourselves this year in Synodex and Agility, which is effectively our growth plan for the year, it’s almost 100% sold, pre-sold in the prior year, which enables a tremendous amount of growth. So I think the key for unlocking growth in the company overall is, number one, pivoting to this larger addressable market where we seem to have a competitive advantage for complex requirements. Number one, and if we've just stopped there, I think we could get the company growing. But then, number two is also progressively investing in platforms and shifting the mix from one-off services where we do kind of – whatever some company may require in shifting to solutions that are repeatable and generalizable for a market requirement as well as platforms where, if you're good you can end up having much more accelerated growth and high quality revenues because of solid margins and large scale of recurring revenue.

Well, one last question, I'll open up to other people, if they're out there. Why don't you comment again on the market value of some of these smaller competitors in annotation that you're competing against what they claim there, these companies are worth in comparison to Innodata, which apparently is able to take business from these companies?

Yes. You know, they're doing. There are a few companies out there that are just doing a wonderful job in terms of market cap management and valuation. There's a large company out there that's valued at 10X or I think seven point[ph] something X revenue, at this point the acquisitions that are being made at 5X to 10X revenue. There are early stage companies that are being founded to exploit this market opportunity that go into things with frankly not a lot, but, are raising tens of millions of dollars with very high valuations. So, I just think it's a remarkable opportunity that, here we are, we've got the skills. We just didn't, – we weren't anticipating really this market. We just knew we had to invest in AI. And now by virtue of that investment, we find ourselves well poised to exploit this from a valuation perspective where, obviously off the radar and that's why I was so excited about the ability to make a significant repurchase of shares this quarter. And the intention to continue to look for opportunities to – when prudent to make additional repurchases at this level of valuation.

Well, great. I’m excited to see Innodata turned to profitability and to growth, and to be in a market which is apparently five to six times higher than the current market you're in and growing at a 30% growth rate versus no growth in the legacy market. So that's, I use the analogy, it's like getting Kareem Abdul-Jabbar or Shaquille O'Neal on your team, just is a game changer because, the coaches are the same, but you just got better players to put on the field.

I share your enthusiasm. Thanks, Tim.

[Operator Instructions] And that appears there are no further telephone questions. I'd like to turn the conference back over to Mr. Abuhoff for any additional or closing remarks.

Thank you, Operator. So I guess to conclude, I just say, we're very pleased with the sequential quarterly progress we've showed in Q4, delivered improvements in revenue, gross margin and adjusted EBITDA, but really what we're excited about, what we're mainly excited about is prospect of delivering a growth year in 2020. And I'm looking forward to sharing with you our progress and results along the way. Thank you.

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