Innodata Inc (INOD) 2020 Q1 法說會逐字稿

Ladies and gentlemen, thank you for standing by. Good morning, and welcome to the Innodata First Quarter 2020 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, Paula. 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 first 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 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 limitation, the expected or potential effects of the novel coronavirus, COVID-19, pandemic and responses of government with the general global population, our clients and the company thereto; 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 and solutions 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 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 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 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, and thank you for joining our call. Today, I'm going to talk about our COVID-19 response, a very exciting momentum we were seeing in our business in January and February, and why we believe we can regain this momentum if everything normalizes.

In mid-January, as news about COVID-19 began to circulate, Doug Kemp, our Senior Vice President, suggested we create a comprehensive COVID-19 response plan. We did that. And in early March, A.K. Mishra, our COO, and I agreed to enable our business continuity plan and our COVID response plan. In doing so, our priorities were: first, to safeguard the health and safety of our team members; second, to provide continuity of service to our valued customers; and third, to maintain, in fact, all of our new AI capabilities, so that as things normalized, we can capitalize on the momentum we have been enjoying in our business.

Thanks to Doug's initial insights, our well-tested protocols for business continuity and the around-the-clock tireless efforts of our global operations teams led by A.K., we successfully enabled our BCP on March 11. We positioned our team members with laptops and encrypted desktops. We increased security protocols to enable people to utilize personal equipment. We increased Internet bandwidth. And we increased cloud-based processing and storage, following close coordination with our customers.

As a result, we now have 94% of our global workforce of close to 4,000 people successfully working remotely, and we have customers who continue to express their gratitude. I expect we will get to 96% by the end of this week.

We started the quarter with significant positive business momentum. Last year, as you recall, we pivoted the company from a publishing services provider to a data engineering company, rolling out new products and solutions to help companies in wider markets, prepare data for AI and put AI to work in their businesses.

In Q1, we've started to see the fruits of our labor in the form of significant increases in the dollar value of new businesses won, increases in the number of new customers acquired as well as a growing pipeline of prospective customer engagements. In the quarter, we've signed $6.6 million of net new business and expansions. This was close to double the new business and expansions we've signed in the first quarter of 2019. And we brought in 88 new customers, which was 40% more new customers than we brought in during the same period last year. What was most exciting about this repositioning was that it leveraged our core competency, the efficient creation of large scale, perfect quality data, which is always relevant to large publishing and information companies, but which was now becoming relevant to virtually any company that had an AI strategy.

With our AI focus, our pipeline soon grew to include banks, hedge funds, online trading platforms and financial services firms as well as drug companies, drone companies, software companies and even movie studios. It was exciting to watch our pipeline grow in this way, to engage with new kinds of companies, to see deals start to close and new customer relationships start to form. Our AI data preparation and AI-based data transformation solutions were clearly aligned to the market's needs, and our rebranding as a data engineering company is resonating.

Our platform businesses, Synodex and Agility, were firing on all cylinders as well, each with significant year-over-year increases in backlog. From an operations and COGS perspective, we were running lean and mean, coming off of Q4 with gross margins of 38%, which is actually a 10-year high. We anticipated that incremental revenue dollars will continue to bolster this with 50% to 80% of incremental revenue, depending on the line of business, contributing to gross margins.

With our strategy clearly gaining traction and momentum, we felt that 2020 had the potential to be the year in which Innodata pivoted to broad-based growth across our business segments.

Now as you can imagine, once the World Health Organization formally declared a global pandemic, new signings quickly started to get delayed or postponed as customers and prospective customers became preoccupied with their own business disruption or business continuity plans.

This slowdown clearly presents a significant level of uncertainty for us. We're all guessing about how and when normalcy returns and the effect and duration of the economic slowdown that is projected. But there is little doubt that we will eventually emerge from this health crisis and business will cycle back as well.

In fact, several important prospective customer engagements that have stalled in mid-March have in just the past week come back to life. I actually think this crisis is going to accelerate global demand for AI services and solutions. We're entering a new era in which AI can help people solve complex problems quickly. AI can spot things people can't. I predict that there will be a great -- much greater emphasis on creating high-quality labeled datasets for AI and harnessing AI to help manage enterprise data. We believe data engineering will be seen as an essential discipline and the key to successfully deploying AI, and that is exactly where we'll be contributing.

Before I turn the call over to Robert, I'll just share a couple of other data points with you. We expect to progress from our current 94% deployment to 90 -- to 100% deployment over the next couple of months as cities where we operate lift their lockdowns. And to reiterate, I'm expecting to go from 94% to 96%, hopefully, by the end of this week.

As we do so, we believe we will recapture about $260,000 of monthly revenue run rate. Importantly, we are confident that the projects that produce these revenues will continue to be available to us and will resume as soon as we can accommodate them.

On the cost side, we will be incurring about $200,000 to $250,000 of monthly BCP costs during the crisis, user costs for PC rentals, remote Internet access and cloud storage that are all necessitated by remote working. We are working on plans to begin reducing these additional costs and/or offsetting them with other cost savings, so that if the crisis persists for longer than 3 months, we will be in a position to reduce these expenses.

I'll now call -- turn the call over to Robert, who will take you through the numbers in greater detail, and then I'll share some closing thoughts. Robert?

Thank you, Jack. Good morning, everyone. Our total revenue was $14.5 million in the first quarter of 2020, which was a 1% decline from $14.7 million in the fourth quarter of 2019. Total revenue was $13.7 million in the first quarter of 2019.

Net loss was $0.4 million in the first quarter of 2020 or $0.01 per basic and diluted share compared to net income of $0.1 million or $0.00 per basic and diluted share in the fourth quarter of 2019. We also had a loss of $0.5 million or $0.02 per basic and diluted share in the first quarter of 2019.

The income before income taxes in the first quarter of 2020 was $51,000 and included $200,000 of expenses in connection with the activation of our business continuity plan across our 12 global locations as a result of the COVID-19 pandemic. And it also included foreign exchange losses of approximately $100,000 from revaluation of monetary assets and liabilities.

Our cash and cash equivalents remained stable at $10.7 million at March 31, 2020, compared to $10.9 million at December 31, 2019.

Thank you, operator. We're ready to take questions now.

(Operator Instructions) And we'll take our first question from Tim Clarkson with Van Clemens.

Just some basic questions. Just in terms of the first quarter, I know there's a little bit of seasonality. With Innodata, isn't typically the fourth quarter seasonally the strongest and the first quarter seasonally one of the weaker quarters?

Tim, that's absolutely right. And that comes about for several reasons. There's usually a push to -- for companies to use up their budgets in Q4, and there are some underlying conferences and kind of proceedings that generate a lot of content. So Q4 is typically high. That's correct.

Right. And when you -- I know you've been shifting the company with this emphasis in artificial intelligence. How do you actually go out if you're working in these new areas like banks and then hedge funds and drugs and so on. How do you actually prove that you're better than the competition? What's that process like?

Great question. One of the most critical things that we're able to do now is, we're able to do demos of our technology. We're able to flood people into our API. We're able to prove to them the capabilities that we're able to bring to bear and with those live demonstrations. So it ends up being very compelling, and people see what is possible. That's in data transformation.

On data annotation, we will often be asked to provide a sample. We will be given a dataset. We'll be asked to annotate that dataset. And they'll ask us and they'll ask some of our new competitors in this space. And what we're finding is in head-to-head competitions or our customer -- our prospects are finding that our data quality is much better because we've been in the data quality business now for decades, quite literally. And a lot of the folks that we're competing against are very high-valued companies, there are start-ups and things, but they don't have our data jobs. So in the head-to-head competitions, we're able to come out very strong, and we're beating them.

Right. You mentioned that you're working with a major brokerage firm and that your -- that they were almost befounded at how much better you were than the competition?

Yes, that's correct. One of our competitors rely on and where they came from (inaudible) legacy. They came from crowdsourcing companies. They came from companies that would provision work out to crowdsource labor, typically for language translation. And then they spotted this opportunity for data preparation for AI and they jumped on the bandwagon. They said, maybe our crowd can do that, too. And the problem is that data is tough. And it's taken us a long, long time to develop the tools and the processes to carefully control the data. Working for the kind of companies that we worked for, Apple and Bloomberg and Thomson Reuters, that there is no tolerance for data error. And as a result, we've built, over time, great processes and great technology for delivering more perfect data, and all of that becomes repurposable as we go to expand in these new markets.

In AI, data cloud is critically important because if you train your AI on bad-quality data, you've got a bad-quality AI solution. It's garbage in, garbage out. The errors not only persist but they promulgate, they multiply, they become like a cancer.

So the critical element here is very, very high-quality data. That's what we're able to do. That's where we have the competitive disadvantage because it's what we've been about for so long now. And the really exciting thing as we get to be who we are and with some modifications and the creations in demo products and APIs and these things, we are now able to lever ourself into this much wider market.

Right. Now how do you compete in terms of costs? Are you cost competitive with the competition too?

We are, and that's also really good. We're -- we always used to say we can be either a fast, good or cheap and 2 out of 3. We're finding in these markets, we can be 3 out of 3. Our quality can be better. We can move and deploy and get things done faster. And we can be either cheaper or equally cost-effective from a pricing perspective.

Right. And are these good gross margins for Innodata than once you do get the business?

They seem to be. The gross margins that we're targeting, that we're showing today, we think we're going to -- as we moved into these new areas, we're going to be in a position to sustain those margins. As we continue to grow some of our stickier solutions and long-term partnerships emerge, our platform businesses continue to grow, we think there's a good opportunity to continue to push those margins higher. And I'm really proud of the fact that the business in Q4, when you -- so we had the COVID costs and kind of the up and down, we'd gotten to an operational efficiency level, producing the highest gross margins in 10 years. So if you take that and now you'd start to put revenue growth with substantial operating leverage on top of that, it gets really exciting.

Right. Right. And you're using artificial intelligence in the legacy businesses already, right?

Yes. In other words, that's where we started. And you may recall that 3 years ago, what we'd like to call our Act 1 was, let's see if we can figure out how to use AI with large datasets internally to drive margins. And for 3 years, we experimented, we succeeded, we failed, we pivoted, we grouped. But we figured out how to deploy machine learning and AI in the service of creating very high-quality annotated datasets. What we did last year was we figured out how do we take that capability and pivot that so that we can use that not as an internal tool, but as an external product with which to address larger markets.

Sure. Can you explain just on a couple of these new areas that we're getting involved in, for example, movie studios. How would artificial intelligence help them?

Sure. Great question. So if we take movie studios, for example, they need to manage vast amounts of contracts and agreements regarding rights and royalties, what images and video do they have the right to use in what kind of channel. It's a very complex area. And as movie studios and television studios start to look out and expand their channels and think about streaming services and new means of distribution, they need to go back and say, well, do we have the right permissions lined up to be able to use this content in this new way. It's not a trivial problem. It was really slowing them down because to figure that out, they'd have to hire teams of lawyers, that would take weeks or months to do the research. What we're able to do is intake all of that data, put some AI on top of it, extract the key data terms out of that and return that in a platform that enables them to do that research almost in real-time.

How about the drones? How would drones use it?

Great question. There's a lot of interest in tracking supply chain and tracking the physical movement of items and predicting supply chain disruption and how intact the supply chain is. And one of the ways of creating that data is to use drones to create -- to capture images of their ships delivering cargo and things like this and trucks being packed and being -- and moving product across the nation. The drones can capture those images, but to turn that into data requires AI that can actually look at those images and recognize what the images are, identify them and assign data values to them. It's very similar to the AI technology that's being used in autonomous driving systems. So creating these systems will give the companies the ability to foresee supply chain disruption and to address that quickly. The drone technology captures in the images, but what the AI does is it turns those images into actionable data.

How about banks? How does it help banks?

So in so many different ways. We're working on several really interesting use cases. One use case is banks are, and especially over the last several years have been faced with some huge regulatory fines and penalties that they'd like to avoid. And the key to avoiding fines and penalties is to know what are the laws that need to be complied with. And when there's a change in the law, being able to trigger the -- operationally, the changes within groups inside the bank who are in charge of maintaining those obligations to then do the right things, so that when the regulators come in and do their audits, everything is in good shape.

There's a huge amount of global regulation, and it's changing over time, and it's been published over time, and it's being revised over time. With our abilities to manage and monitor that change and help banks understand that change as it's occurring, they're in a much better position to then comply and to ensure they're doing the things to comply, and thereby, avoid billions of dollars of fines.

Another great use case is banks have a loan documentation. They've got bond, debenture, indentures. They've got tons of stuff that is written in the form of very dense, very lengthy legal contracts. And again, much like the use case in rights and royalties, they've depended historically on teams of lawyers to interpret these things, and that takes time, and it takes a valuable time when they're losing time reacting to a market change event, for example. With our systems, they're able to extract key data points from those documents, push those data points into a platform, which we call bot analytics and react very quickly to those. We put in a system that does exactly this in one of the largest hedge funds in the world, I can't use their name, unfortunately, but one of the largest hedge funds in the world just in February of this quarter. And they loved it. So we see a lot of opportunity there as well.

Sure. One last question. Can you comment -- I know you've hired some new salesmen. How many new salesmen did you hire? What kind of competencies do they bring? And are they getting new business?

Yes. So we brought in 3 or 4 new people, and I'm really looking -- I was hoping to be expanding that further. We're going to take kind of a little slow until we see how things are shaking out. But they're getting good traction. They're starting lots of fascinating new conversations. One of the things that they bring to the table is network and the fact that they're not from publishing. They're from banks, and they're from Silicon Valley, and they've got different kinds of experiences and different kinds of networks, and that's been really helpful to us.

I talked in the call a little bit about how a few things have been stalled in mid-March are starting to unfold that. And just last week, 2 examples of that were one very, very large technology company, that's exploring, embedding our solution into their -- one of their go-to-market solutions. And another is a very large insurance company. And that use case has nothing to do with Synodex. It's completely different from that. And these are leads that are being generated and worked on by our new sales force.

Sure. Well, good. I've been hogging up the call. So I'll see if anybody else wants to get in. Otherwise, obviously, it's an improved quarter, and as this COVID stuff gets through it, hopefully, we'll see a significant better sales and earnings.

(Operator Instructions) We do have a question and that will come from Joe Furst with Furst Associates.

Could you explain a little bit on your other businesses and tell us a little bit about how they're going?

Sure. Happy to. So the real good news in both Synodex and Agility as we were approaching the year was we had, in both cases, sold booked work that the value of which exceeded the revenue that we had done the year prior. So very good traction, very good pickup.

In Synodex, we had branched out to a new use case, a new segment of the market. That was very positive. So lots of very, very strong momentum in both of those businesses. Our Agility business was ranked by an independent analyst firm who surveys customers to draw their conclusions. We were ranked as the #1 product in its industry, which was just mind-blowing when you think about the fact that the 2 largest competitors in that industry are $800,000 company and a 200 -- I believe, $250,000 company. And we're there at $10 million with the best product out there. So we were -- we've done some yet additional improvements to the product that made it very strong in an area that we felt we were a little weak in. And sales were going very, very well, very strong.

Synodex was more impacted from a revenue perspective on the supply side than Agility was by virtue of the nature of the business. Agility is a little bit more impacted in terms of the need to sell new business, and sales have been a little bit tough since mid-March. But -- and on the Synodex side, we're solving the supply side problems that -- closing that gap from 94% to 96%, hopefully, by end of this week is largely on the Synodex side. And we're confident that and cautiously optimistic that as the world starts to gain its footing in the new normal, we're going to see sales progress in both of those areas as well.

On the Synodex side, it was interesting, we had a couple of customers that we weren't able to take care of by virtue of not having access to office equipment, but we've scrambled. We've come up with some workarounds for them. And they've told us that as soon as we're back to business, they absolutely need us engaged toward -- critical to their smooth operations, their ability to process life insurance applications, which has been on the rise recently. So really good momentum, and our efforts now are to conserve that momentum and to put ourselves immediately back in a position to be driving those businesses forward as the crisis kind of settles in or alleviates.

And at this time, I'd like to turn the conference back to Mr. Abuhoff for any additional or closing comments.

Thank you, operator. Sure. I'll quickly provide some key thoughts to close. Just first, because we were well positioned to address the crisis and because we triggered our BCP early, we really truly came through for our customers. Our teams are now 94% fully functional. We expect this to get to 96%, hopefully, end of this week and then to progress to 100% over the next couple of months as lockdowns have softened. This delta is now 6% delta representing about $260,000 of monthly revenue run rate. And I'm confident that as soon as we're able to accommodate it on the supply side, the demand side is going to be intact.

We entered 2020, seeing strong positive market validation for our new positioning as a high-value AI-based solutions provider. As a result of COVID-19, we're in a tough business environment for sure. But I think we can take -- make meaningful progress in 2020. We're continuing to book the new business at a lower level than we were in January and February, but we're seeing some signs that that's going to improve as well.

We'll be continuing to optimize our cost structure to align to revenue curves. But against this, we're going to protect our key new skills and capabilities. So that as the world returns to normalcy and people get settled into the new normal, we're in the best possible position to aim to resume our strong momentum. We're bolstered by the fact that 83% of our revenue is recurring in nature or subscription-based and our customers serve diverse markets. We presently have $11.1 million in cash. In the current quarter, we produced $700,000 in cash from operations.

So again, everybody, thank you for joining. I guess I'd just make one other observation. I actually think that the COVID-19 crisis is going to end up shedding a light on how powerful the tool AI is to solve complex problems. And as a result of this, we're going to end up with probably the best case study for AI ever imaginable. I think AI is going to accelerate. And I think we're going to be in a great position to respond to what will be that increased demand. Thank you all for joining today. Please do stay safe and continue to be optimistic and persevere, and let's look forward to continuing to build momentum through 2020.

Thank you. And today's conference is available for replay from 2:00 p.m. Eastern Time today to June 13, 2020, at 2:00 p.m. Eastern Time. You may access the recording by dialing (719) 457-0820 or 1 (888) 203-1112, using passcode 9231591. This concludes today's conference. You may now disconnect.