Good morning, and welcome to the Innodata Third Quarter 2019 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, ma’am.

Thank you, Ian. 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 third 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 the Private Securities Litigation Reform Act of 1995. Forward-looking statements include, without limitations, any statement that may predict, forecast, indicate or imply future results, performance or achievements. These statements are based largely on our management’s current expectations, assumptions and estimate and are subject to a number of risks and uncertainties, including, without limitation, 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 are 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 give rise to requirements for our services; difficulty in integrating and deriving synergies from acquisitions, joint venture 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 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. Innodata has 30-plus years of history, providing high quality data to some of the world's largest and most demanding companies. And over the past couple of years, we've been harnessing AI and machine learning capabilities. The AI/ML revolution that is transforming every company and every industry is still in his first or second inning and exponential and accelerating growth is expected. Our history of expertise in managing, curating and securely processing large amounts of data and harnessing AI has positioned us ideally to take advantage of this secular trend. If you take a look at the new Innodata website we launched last Friday, you'll get an idea of how our core capability combined with AI work we've been doing have enabled us to refresh our offerings in order to now address wider markets that are fast growing and expected to be worth multiple billions of dollars within the next five years. For the last two years, we've been on a path of transforming our business in order to become a leader in these fast growing markets. This journey began with us creating AI-based solutions for our own internal use and our success here enabled us to remove several million dollars of costs of manual human labor management and infrastructure while at the same time improving the quality of our offerings. Our success with developing these AI capabilities has now enabled us to package them with solutions that we can take to a wider range of industries and applications. And we are seeing an excellent response from the marketplace. By way of example we are on track to close this year over $1 million of opportunities for the new services listed on our website with companies that are outside our traditional publishing sector. In 2008,…

Thank you. [Operator Instructions] We'll begin now with Tim Clarkson from Van Clemens. Please go ahead.

Hi, guys, just wanted to ask, my clients are curious, they hear about IBM and they hear about other companies they're players in artificial intelligence and they're skeptical, how a little company like Innodata would have any expertise in artificial intelligence. So what are the skill sets that Innodata has that makes you believe that we can make some money in this area? Robert O’Connor: Tim, great question. Thank you for that. So a couple of things there. First of all, we are talking to many of the large players in artificial intelligence about working with them. There are channel partnership opportunities we have, because we do different things. If you take a look at our new website what you'll see is we do several things with artificial intelligence starting with helping people build their AI models. So there're people who are building AI models, they need to train those models. And what they need is a combination of AI, human expertise and a secure data infrastructure in which to do that. We bring all that to the table. In addition to that, and on top of that, we're looking at data transformation and data curation. And when we're performing data transformation data curation for people, we're using the AI models that we've built oftentimes working with the frameworks that are produced by some of the very large companies. But the models that, we've built and that we've engineered, we maintain and we manage that turn documents that people now read into data that computers can read. We're helping to curate data, master data that's at the core of companies success like CRM data that again works with the combination of our trained experts and our robust trained AI models. So within the ecosystem and there are people that produce maps showing how this ecosystem is emerging. There is most certainly a play for us. We're seeing lots of pipeline opportunity, as I just said in my prepared remarks, and it's a large and fast-growing ecosystem. AI products and services is expected to be $180 billion by 2024 and we think there is absolutely a play for us within that ecosystem.

Okay. Now, I know you got some contract specifically with these life insurance companies. How are those contracts going?

Going very well. What we're – there have been a few developments in there two of the three largest life insurers in the quarter have increased their business with us, and we plan to ramp-up into that beginning late in the third quarter and into the fourth quarter. And the third of the three largest life insurers is exploring working with us now. Apart from that, we see another related segment that could also benefit from our services and we're in co-development with two of their largest – two of the largest companies in that related segment to begin working with them as well. So, excellent progress there.

I know that you had on your website that you're doing some work in data annotation and you had three different types of business that you showed. How many different customers are we working with right now in that area?

So a lot of the work that we've done historically is in fact data annotation. Increasingly, though what we're seeing is an opportunity to work for – to provide data annotation services to companies that are using the data not as part of their data product, but they're using the data in order to build models. We're working with a good number of companies that are in that category, and we're working across text, video, image and audio as well.

When do you expect to start seeing actual revenue increases that we'll see in the actual quarterly results?

I think that we should be looking towards first quarter for that. Yeah.

Yeah. Now we talk before about sort of that $15 million to $16 million level where you start to make some money and really show some growth. I mean, is that a reasonable expectation to hit? Obviously, it's too early to guarantee anything.

So we're working our 2020 budgets now, but we are targeting next year to be a growth year across all of our segments. And we think that growth is going to be – in large part by virtue of the fact that, we're using the AI capabilities that we've been building over the past couple of years and have deployed primarily internally. And we're now turning those into externally facing product offerings and service offerings that go to a much larger addressable market The inhibiting factor that we've really always had is a fairly circumscribed addressable market. And what this transformation what the pivot enables us to do is to broaden that play very significantly. And to perform a function within this market that's very, very much in demand.

Now I noticed in the quarter that Agility had nice sales growth. I mean, do you expect that to continue?

We do. Agility is doing real well. We're forecasting growth in the fourth quarter we're going to forecast growth in the business continually through next year. And that growth is being fed by two things principally. First retention, our overall net retention continues to approve – improve. It was over 90% this year, which is exactly where we want – this past quarter which is where we want it to be. On top of that, we're seeing very significant improvements in terms of lead flow everything from web traffic which was two times this year than it was last year to lead flow from marketing-qualified leads turning into sales-qualified leads, and improvements in bookings that follow that. So what we're looking at is really being in a position to have all that plumbing in place and to start accelerating growth through the next year.

Now, what would you say is you're differentiating characteristics of that business that allows you to compete with the bigger guys that you're competing with?

Well, what I look to – I have opinions about that but what I look to is what the market's telling us. We're now ranked the number one easiest to use media and influencer targeting platform in the world and we're considered to be – and this is the analysts talking we're considered to be the momentum leader based not only on growth, but also on customer satisfaction ratings. So there are some things that we do in order to achieve that, but that's market telling us that we maybe small now, but we've got an opportunity to capture a share of this very large market.

No. I know seasonally fourth quarter has always been one of your better quarters. I mean, is it shaping up the same way this time?

Yeah. I think we're going to have a good fourth quarter. There's – in each of the businesses we're seeing opportunities for growth and for expansion. But a lot of what we're going to do with this transformation is we're going to find less satisfaction in $100,000 here and there of growth and we're going to be looking to driving much more substantial growth over longer periods of time.

Right. Now, are the size of the deals that you're seeing in AI are they bigger than your historic legacy market?

It depends. The legacy market has always been characterized by lots of small deals and occasionally a very large one coming along. I think that we're going to – the deals that we're now looking at are larger than our small deals. I don't know whether we're going to see deals that are comparable to our larger deals which we've had maybe two or three over the last decade. That remains to be seen. But I'm looking for $100,000 to $300,000 as a sweet spot. If we can collect a lot of those we're going to be in great shape.

And one last question. I mean what kind of percentage of business do you think is repeatable business versus project right now?

In terms of the business right now or as we look forward?

Yes. No well both I guess.

Rob, do you have any recurring revenue number right now. I'll -- while Rob gets that number for you I'll... Robert O’Connor: I only have for Agility it's.

I'll talk about going forward. I think the -- what we're seeing in terms of data annotation is that there is a continuing need. It's not a one-time event to build a model whether that's a text analytics model, a video model, autonomous driving chat bots whatever it is there's initial training but then there is maintenance that's critically important in terms of maintaining that model as a high-performing model. So we are seeing recurring revenue opportunities there. Where we're positioning our data transformation offering is absolutely a recurring revenue play. We see that as an embedded functionality that's API-driven that will enable us to continually process text and turn into machine processable data. So we're very focused on recurring revenue. We recognize how critical that is and we think that the new product services architecture is going to enable us to drive that further.

One last question and then I promise I'm done. So can you give me an example of how you'd be working with a customer? You obviously don't give the name but where that would save the money? And how it would save the money?

Sure. So if you look at the our offerings in terms of intelligent automation as well as data transformation, what people are looking to do is reinvent knowledge-intensive processes. So really what we're able to do there is we're able to share with our customers, the things that we've learned over the past couple of years integrating AI, which is how does AI work with people, how do you hybridize machines and humans how do you use AI not to replace people but to augment them? And we've learned an awful lot. We learned from our mistakes and we learned from our successes and we've built that into our platform and we're now able to present that as a capability to customer base.

Right. Why don't you just explain and we talked about -- when I we talked with the Agility President about the savings in cost and the improvement in quality. I don't know if you remember that conversation but I'm sure you deal with the -- what should -- were you able to do at Agility?

Sure. So in the Agility business we've got a few assets that we're working with. One of the assets is we've curated a database of global influencers and journalists. And the fact of that that database is of tremendously high quality and tremendously addressable, meaning that if someone has a particular message that they're looking to amplify into the world as a marketing initiative, our database enables them to very discreetly isolate the people that are most likely to be interested in that message and the most likely to amplify that message in both social media and traditional media. And what people are finding is that the return on that effort, the return on that investment is much higher than sending out a generic wire that may or may not be read.

Sure. I know you also mentioned real simply that they are able to cut their workforce in half and actually improve the -- how fast they could respond to queries too.

Well, that's right. So there're a few things that are going on and this really is true across our businesses. People are looking to take processes that had been labor-intensive, that had been slow and arduous and they're looking to move those into being able to respond and as close to real time as possible. And what are the impediments to that? One of the impediments in -- still in many workflows is that you take -- you need people who have expertise to read and to process textual data. A lot of the work we're now doing in data transformation and in intelligent automation and then by extension also in entertaining other people's data for their own models, a lot of that work is geared to making businesses digital, enabling them to deliver the promise of additional transformation, which includes lower operational costs but also very, very quick response time to customers and very quick response time to changing market conditions.

All right. Okay. I am done. Thanks.

Thanks, Tim

Thank you. [Operator Instructions] It appears we have no further questions at this time.

Thanks, operator. I'll just quickly add a couple of concluding thoughts then. In our fourth quarter call we will share with you our goals for 2020 and the metrics we will use to track our progress. As you know, the operating leverage in our business allows us to translate 60% or more of incremental growth to our bottom line. The increase in our sales force and our ability now to target large fast-growing markets is essential to our goal of showing accelerating revenue growth in our business next year. And in addition to driving growth, we intend to continue to drive operating efficiency as well and we will be prudent stewards of our capital. With -- our Agility and Synodex businesses have inflected and are expected to be EBITDA positive in the fourth quarter contributing to what is likely to be another sequential increase in the EBITDA in the fourth quarter. And we're at an exciting time and our Board, our management and our team members are tremendously enthusiastic about our prospects and the new opportunities we're seeing as a result of our new initiatives. Thank everybody. Look forward to being with you next time.

Today's conference is available for replay from 2 p.m. Eastern today to November 7, 2019 at 2 p.m. Eastern. You may access the recording by dialing 719-457-0820 or 1-888-203-1112, using passcode 3970376. Again the numbers are 719-457-0820 or 1-888-203-1112, passcode 3970376. This concludes today’s conference. You may now disconnect.