Innodata Inc (INOD) 2020 Q4 法說會逐字稿

Good morning, and welcome to the Innodata's Fourth 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, Mary. Good morning, everyone. Thank you for joining us today.

Our speakers today are Jack Abuhoff, CEO of Innodata; and Mark Spelker, our CFO. We'll hear from Jack first, who will provide perspective about the business, and then Mark will follow with a review of our results for the fourth quarter and the 12 months ended December 31, 2020. 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 management's current expectations, assumptions and estimates and are subject to a number of risks and uncertainties, including without limitation, the expected or potential effect of the novel coronavirus COVID-19 pandemic and the responses of governments, the general global population, our clients and the company there too; that contracts may be terminated by clients projected or committed volumes of work may not materialize continuing Digital Data Solutions segment reliance on project-based work and the primarily able nature of such contracts 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 the 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 arise 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 and 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 results in the unauthorized disclosure of consumer, client, employee or company information or service interruptions and various other competitive and technological factors and other risks and uncertainties indicated from time to time in our filings with the Securities and Exchange Commission, including our most recent reports on 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.

Good morning. Thank you, Amy, and thank you, everybody, for joining our call. In 2020, despite the dramatic economic slowdown and anemic pace of business, Innodata succeeded at growing revenues, growing earnings and improving its balance sheet.

Today, we're reporting year-over-year revenue growth of 4%, a $2 million improvement in pretax earnings and an increase of $7 million in cash balances over 2019. In a year that brought us once in a century pandemic, record-breaking unemployment levels and millions of shuttered businesses, we're pleased with this result.

Exactly 1 year ago today, we implemented our COVID business contingency plan, shifting 4,000 global staff to remote working within a matter of days. We did this before the global lockdowns and before the spike in cases and deaths. We were among the first companies to take this very difficult decision, which, as we now know, turned out to be prescient. Thanks to an indefatigable and immensely talented global team, we figured out remote working, missing not a single customer deliverable along the way. And we made significant strides with our AI product strategy.

As a result of focus and investment, we believe we emerged from 2020 stronger and more capable than ever and optimistic about our opportunities. And we believe we are positioned for aggressive organic growth across all of our business lines.

In the fourth quarter, we got a glimpse of this acceleration, with revenue up 5% sequentially over Q3, pretax earnings of 663% and cash up to $2.2 million. We are very excited about the future because we believe tailwinds for each of our businesses are stronger than ever before.

With respect to our DDS business, the AI data training market is estimated at $1.9 billion this year and expected to grow to $3.2 billion by 2023, essentially proxying the enormous growth expected in AI overall. Similarly, the global data annotation tools market was valued at $695 million in 2019 and is projected to reach $6.5 billion by 2027, which is a compounded annual growth rate of 33%. The document analytics market is also fast moving and dynamic, expected to grow at a CAGR of 48% from 2020 to 2027, reaching $12 billion.

The strength of our offerings in these spaces is validated by the fact that notwithstanding the pandemic, we acquired 20 new customers for AI-related services in 2020, more new customers than our Digital Data Solutions business had acquired in the past 3 years combined. We expect that by getting our foot in the door and executing well with these new customers, we will see significant expansion in our business with them.

In our Agility business, we believe we have the best-of-breed product offering. G2 Crowd, which says it is the world's largest tech marketplace, where businesses discover, review and manage technology, has this to say about Agility based on user reviews. It says that Agility meets the needs of customers better than Cision or Meltwater, the 2 largest companies in our space with combined revenues of over $1 billion. It says that Agility is the preferred option when comparing quality of ongoing product support. And it says that reviewers prefer the product direction of Agility over both Cision and Meltwater based on feature updates and road maps.

Indeed, Agility is now regularly winning business against these leading companies. Because of the traction we are seeing in this business, we're significantly increasing our sales and marketing efforts. Our plan calls for achieving a revenue CAGR of over 40% over the next 5 years in this business.

In our Synodex business, we are very excited about the launch of our next-generation Synodex platform for extracting analytical data for medical records. This next-generation platform, which will be AI-enabled, will allow us to deliver increased throughput speeds at lower cost, the holy grail in our market. Consequently, we think it will enable us to address several new markets that would benefit from faster, more automated, but highly accurate medical data extraction, significantly expanding our total addressable market.

In addition to growth within the insurance vertical, it will allow us to address needs in the health care sector, which is increasingly seeking to search, analyze and interpret fast volumes of patient data, improve clinical documentation and make computer-assisted coding more efficient.

The global artificial intelligence in health care market is forecasted to reach a market size of $62 billion by 2027, up from $3 billion this year with a CAGR of 43.6%. Consequently, we expect our Synodex revenues, which grew 22% this year, to significantly accelerate from that pace.

To sum up, we are seeing a blue sky growth trajectory in the industry segments we serve, and our offerings are seeing strong customer adoption. We have positioned the company not only to participate in its growth but to outperform it by gaining share. The 2 key areas of focus to enable us to accomplish our execution goals are: one, investing in our people and significantly expanding our sales and marketing efforts to allow us to reach an ever-expanding pool of customers; and two, investing in technology to maintain and enhance our product excellence and leadership as well as enable us to scale our business for growth.

In terms of people, our biggest investment will be in sales and marketing. For most of 2020, we had 15 people in sales. Our 2021 budget by contrast anticipates ending 2021 with a sales team of 98 in total, 63 sales executives, 25 business development resources and 10 sales managers and sales enablement directors. We expect this will deliver significant returns in future years.

In terms of our technology and solutions, we are focusing on 3 key areas: first, we have been building what we expect will be the best-in-class data annotation platform for text. We'll incorporate AI in ways that existing tools in the market do not reducing the cost of data annotation and improving consistency and quality of output because our data annotation platform will be enabled by our proprietary AI platform that I'll talk about next, we will have auto tagging intelligence that will apply to both classical and generative AI tasks. We started building this in 2020, and we plan to launch it commercially in June. We already have charter customers lined up. We anticipate the platform will be a source of competitive differentiation and potentially new source of SaaS licensing revenue.

Second, we have been building a proprietary AI platform we call Golden Gate. In a nutshell, Golden Gate "reads documents and text and tells you what the documents are about." Golden Gate accepts any kind of documents, images, PDFs or web copy, it doesn't matter. And it performs a series of cognitive tasks to extract intelligence that people can use for generating inferences and powering analytical applications.

In terms of AI, it is truly state of the art, serving up no-code AI with transfer learn built on generative language models we have developed and perfected over the past 5 years of deploying industrial deep neural networks. Golden Gate will be the AI under the hood that powers our data annotation platform and brings AI capabilities to our industry platforms like Synodex and Agility.

Golden Gate will also be the foundational technology for work we perform for customers. The main benefits of the platform is that it's no code, so it doesn't require a large number of data scientists to build models or require a data science platform to orchestrate models and update models. Using Golden Gate in combination with our SMEs, we were able to build high-performing cutting-edge models that address real-world problems.

Our 2021 journey is through AI-enabled Synodex, Agility and our data annotation platform using Golden Gate. In 2022, we intend to commercialize it further as both a customer-facing technology and as an engine for other potential industry solutions.

Lastly, we're investing in a resource management platform geared specifically to managing remote staff and freelancers, allowing for accelerated scalability. Pre COVID, our operating model was to almost exclusively use full-time employees working from large production centers. But COVID forced us to find another way, and we've made lemonade when we got served lemons. We're now practically 100% cloud-based and remote, which means lower fixed operating costs and greater scalability. We expect to fully fund all of these investments from our internal resources without the need for outside financing.

I'll now turn the call over to Mark Spelker, our CFO.

Thank you, Jack, and good morning, everyone, and welcome to our earnings call. I'm going to briefly go over some of our historical results for the fourth quarter and the year ended December 31, 2020.

Total revenue was $15.3 million in the fourth quarter of 2020, a 5% increase from $14.6 million in the third quarter of 2020. Total revenue was $14.7 million in the fourth quarter of 2019. Net income was $1.2 million in the fourth quarter of 2020 or $0.05 per basic and diluted and $0.04 per diluted share compared to a net income of $0.2 million or $0.01 per basic and diluted share in the third quarter of 2020 and a net loss of $0.5 million or $0.02 per basic and diluted share in the fourth quarter of 2019.

Total revenue for the year ended December 31, 2020, was $58.2 million, an increase of 4% over $55.9 million in 2019. Net income was $0.6 million or $0.03 per basic share -- per diluted share in the year ended 2020 compared to a net loss of $2.1 million, or $0.08 per basic and diluted share in 2019.

Cash and cash equivalents were $17.6 million at December 31, 2020, and $10.9 million at December 31, 2019.

Thank you very much. I appreciate your patience.

(Operator Instructions) And we will now take our first question from Dana Buska with Feltl.

My first question I have is around your -- developing your sales force. I was wondering if you guys have any type of sales goals or revenue per sales person that you're targeting right now?

So yes, in the different businesses, the sales quotas are different. In the Digital Data Solutions business and the Synodex business, people come in with roughly $1.5 million quotas. And then quotas are designed around their account base in subsequent years, meaning the bigger the accounts the bigger the quota. In the Agility business, people come in with quotas of about $450,000 per year.

Okay. Great. And with the ramp-up of your sales people, how do you see that going? And how long do you think it's going to take before each people will be reaching their full quota?

So I think it's going to be a continuing process to bring people in. It's not going to happen automatically. We're being very selective in who we hire, as you would expect. But I think as we said in the call, we plan on exiting the year with 98 people. 63 of those people would be account representatives, 10 executives and then 25 BDRs supporting them 10 sales managers and enablement people around that.

So I think what we're going to do is we're going to hire well, we're going to hire selectively and we're going to be making sure that our investment is paying back adequately as we move forward. We see compounding value of new customer wins is being a very important part of the value that we're creating here. And we're going to be sharing with you in each of the quarters of next year exactly what our investment level is and what return we're obtaining on that investment.

Okay. Great. I'd really like to see that you're working hard and ramping up your sales force because it sounds like you have such an excellent opportunity in front of you right now, especially what's going on with AI. It seems like it's a very exciting market right now.

I do have one other question around how you guys look at your revenue and how you're able to anticipate one of the things in the past as your revenue is a little lumpy. How do you see that now with the AI offerings that you have? Do you anticipate that your revenue will be, should I say, more predictable going forward?

Yes. I think when I contrast what the road ahead looks like with road behind us, the -- it's a very stark contrast. In the past, when we were creating high-quality data for publishers and information companies, there were really 4 companies that constituted our market. After that, they became very, very small. And every now and then, one of those companies would have a huge project, and we had quarters where half our revenue was on a single onetime project from a single customer.

When I look forward, it's a very different view. When I look forward, any company who's building AI has now an appetite for high-quality data. It's not 4 companies any longer. It's every company is building AI.

And when I look at the industry segments that we're now serving and where we're seeing strong customer adoption, all of those segments are predicted to grow very strongly over the next several years. So I think that, that lumpiness -- I'm never going to say that it won't be there because there are some very large projects that we're looking at even now. But I think that diversity of customers, the diversity of customer base and use cases is going to help take care of that.

(Operator Instructions) We can now take our next question from [Jerome] of White Bear Fund.

Congratulations on the results, long-term investor in the company. I'm just curious, maybe this is a Mark's question. As you're ramping up all the additional people, give us a little flavor, if you could, on the ability to stay positive cash flow as that happens throughout the year?

Yes, that's a good question. Go ahead, Jack.

Go ahead, Mark. Please, go ahead.

Okay. Yes. And I'll comment and you can certainly augment. We're going to make these investments selectively, as Jack said, with a view towards long-term growth. And when I say long term, I mean over the next few years. We will expect to get some dividends out of our investments in the latter part of 2021. And if we are not starting to see returns commensurate with our expectations, we will adjust accordingly. Jack?

No, I think that's fair. I think in terms of return that we're expecting on the sales and marketing initiatives, the returns are extremely attractive. As Mark said, we're going to be careful. We're going to be prudent. We've got a lot of metrics that we're going to be tracking around that. But we see a very high, very compelling rate of return that we expect to come from what we're doing. And we've got an eye on free cash flow. And I think we're showing that now with the results that we're obtaining.

We'd like cash in the bank, and we intend to spend it very selectively. We're hopeful that we can stay free cash flow positive when we look at the year as a whole, but we've got the resources on the balance sheet that we require if making investments that are proving themselves almost immediately relative to our tracking metrics. If that's happening, then we're investing. We've got the resources to do it. We don't need to go out and do an equity offering or bringing debt. So we're pretty excited about the prospects and where we are to.

That's great. One last question, I'll let you go as the -- out of the 63 sales reps that you're looking at having at year-end for the new hires, where are you getting the good ones from? Just curious of other industries or what are you seeing out in the marketplace? And then I'm done.

The answer is, there's -- unfortunately, there's no single well that you can tap for great sales people. We're being very creative. We've got a number of recruiters who we've built relationships with that are very, very helpful. And we've got people that we brought in, in leadership position who have done this before, and that's just wonderful.

We did a press release several weeks ago about hiring Tom Perchinsky as our Chief Sales Officer. When we brought him in and we said, "Hey, Tom, here's where we are with our product." Our product is best-in-class. It's a $4 billion market. We're $11 million. And now the really tough thing is going to be building a sales organization.

And Tom said -- he said, I don't want to devalue my contribution, but this isn't going to be that tough. I've done this several times before. I have a playbook for this. And I know where to get great sales talent. So Tom is hard at work. He's executing. He's tapping a few wells that would not have occurred to me, and I'm very optimistic that he's going to be able to deliver.

Great. Well, thanks. I love the growth strategy and quarter was really good, much better than I expected based on you starting this ramp up. So keep up the good work.

And we can now take our next question from Tim Clarkson of Van Clemens Capital Management.

Just wanted to ask, you've got 20 customers in this new AI area. How many of those customers would you say have already migrated from kind of the startup order deal to starting to give you more significant business out of the 20?

I think we're in very early days with most -- all of those customers. That said, I think that there is very significant potential for growing business with most -- all of them. I think what's critical is landing and expanding. I'm going to be looking very carefully at how many new customers we're bringing on in each period because I think the potential for expansion is that great. And there's so much compounding value that will come from those new customer wins. So early days on the 20, but expect good things from that.

Sure. Now on the salesmen hires, can you tell us how many salesmen you've actually hired so far?

I don't have that number handy, where we exited -- we had an average of 15 towards the end of the year. I think in our DDS business, we brought in another 3. In the Agility business, we brought on another small handful. In the Synodex business, we have 2 new people, who are going to be on the sales effort. Prior to that, we had none. So we're on our way, but we're very much heads down on the recruiting, interviewing, assessing, testing and soon to be training.

So maybe like 7 to 10, something like that?

Yes. That's probably right. Probably closer to the 7.

Okay. Sure. That's fair. Now in terms of your differentiation on artificial intelligence, it's hard for us non-technology guys to understand it. So let me explain what I think, at least, in terms of the processing information, what Innodata does? And you correct me. So when I look at the experience that Innodata has, for example, is digitizing books, which is the most well-known, probably not the most kind of work you do, but it's the one that guys like us understand, there's 3 processes in terms of refining the information. One is having highly skilled experienced people in the Philippines and India that their top college -- top of their class have 5, 10, 15 years of experience, very detail-oriented, and they go through and they're translating all this information accurately. And so there's that human element of good people with experience, and that's the first phase. And then there's a second phase where you use AI to fair it out any mistakes that they may have made, and that's a proprietary process that you've developed internally.

And then lastly, you make sure that you have experts in the particular fields that are making sure that even though they may have got the information accurately translated that they got the meaning accurately. So you have lawyers looking at legal documents and doctors looking at medical documents and so on. Is that what you do or is it more complicated than that or what's the secret sauce that Innodata has that allows them to be more accurate?

Yes. Great question, Tim. So I don't think that it's more complicated than that. I think it's actually pretty simple, but I think it's a lot bigger than that.

Okay.

You build AI applications with data just like you build conventional applications with programmers. So when we think about building an application, you think about programmers. You think about people who can code in Java, who can code in Python.

When you go to build an AI application, though, there is no programming. You're building it with data. And you're building it with data that's been very carefully cultivated in order to be very exact and to be very, very high quality. If you build it with low-quality data, you get a low-performing AI application. If you build it with high-quality data, you get a high-performing AI application.

So we've built Golden Gate, which is cutting-edge AI. We're combining that with our subject matter experts, people that we might have, in earlier days, used to do things like ebook search. But now we're combining those people with the Golden Gate technology to create cutting edge, high-performing AI models and very high-quality data that can be used to train those models. And we're doing that in 3 layers. We're doing that for people who need high-quality data to train their own models. We're doing that for people who don't have the data sciences' team but want AI solutions to help them run their businesses better. And then we're also taking that AI and we're building that into industrial platforms like Synodex and Agility will soon be that are powered by AI.

So it's very much tethered in our legacy, in our history of having subject matter experts accessible to us around the world. And it's very much tethered in our culture of data quality -- of being fanatical about data quality of having the processes and technology to create that high-quality data. And now instead of delivering back to the market ebooks, we're delivering to them high-quality training data. We're delivering to them AI solutions, things programmed with data. And we're delivering AI industry platforms that generalize the AI into platforms that do things for people that they require to be done in order to run their businesses better.

Okay. Well, it sounds like it's evolved into a much bigger deal to put it simply. So...

We're really excited about it. And we think it's just a huge opportunity for all of us to be participating in this, and it's a lot of fun. It really is.

Sure. You mentioned in the previous calls that you've gotten 1 of the big 5, and that relationship was good and it was evolving. Is that still true?

It is, and we're very excited about it. We're hopeful that we will continue to see that evolve, and we'll continue to see new use cases that we're being asked to help them with. And we feel that way, not only about that relationship, but as we discussed a few minutes ago, with most or many of the other 20 new customers we brought in. And of course, we're not stopping. Our marketing efforts have really evolved, really picked up. We're doing great work on the marketing side. We're seeing a fairly continuous funnel of new customers for whom we're building prototypes and for whom we're doing proofs of concept.

Sure. Sure. One last question. This is more of a stock market question. In terms of the kinds of valuations you see for companies that do something similar to Innodata, what would be a typical -- I guess, the value of these things on price to revenue, what's the typical price to revenue ratio that you see publicly and in private market valuations?

Good question. So on the public company side, we saw most recently, Lionbridge sold at 5x revenue. They are $200 million business, sold 5x revenue. We see Appen, it was publicly traded. I think they've got about $440 million of revenue, and they're valued at $3 billion. So it's about a 6-point -- whatever that would be 6 to 7x revenue multiple. Beyond that, there are companies like Sprout Social, $100 million of revenue with a $2.7 billion valuation. Meltwater just went public with $340 million of revenue, valued at $1.6 billion, I think. That's about a 4.6x.

On the private side, on the M&A side, Cision went private, I guess, end of last year at about a 4x revenue multiple. They bought TrendKite at a 9x revenue multiple. So that's roughly what we're seeing.

Right. One last question. I assume that you compete with these people, and you think that in a lot of respects, you're superior to a lot of these companies in terms of the -- being able to take business from them and so on.

Yes. Well, it's interesting. What we're seeing on the media intelligence side is very clearly, where analysts are saying we've got a great product and we provide great support around it, and customers seem to be appreciating that and valuing that, which is why now it's time to take the gas pedal hard on the sales and marketing side and Tom is having a lot of fun with that.

On the AI side, we're kind of seeing AI that was first really consumed aggressively by very early innovators now kind of moving through the adoption process to some early adopters. And we think we've got what it takes to make those early adopters happy. So when we're competing against some of these companies for their business, we're winning. So again, that's where we see the opening to dial up our investment in bringing more customers, land more, critical, critical that we -- I want this year not to bring in 20 new customers, I want to bring in many more than that. And the ones that we're bringing in, I want to expand our relationship with aggressively.

And with no further questions at this time, I'd now like to hand it back to Jack Abuhoff for any additional or closing remarks.

Thank you, operator. So yes, I'll quickly provide some closing thoughts. We're very pleased to be able to have delivered growth in revenue, earnings and cash in 2020 and in Q4 sequentially and year-over-year. We're also really excited about where we see the business going. We're expecting to deliver growth in 2021 on a consolidated basis and across each of the business segments. And we'll be making investments to position the organization for continuing growth in the coming years. We intend to finance these investments fully from internal resources.

As I mentioned, beginning in Q1, we'll be sharing with you the investments that we've made in the quarter to help you understand the underlying cash generation capability of the business and its inherent operating leverage, which are wonderful characteristics of the business we're in. And we'll be sharing with you how we think about return on that investment.

We've got a very strong balance sheet. We've got $17.6 million in cash at the end of Q4, which was an increase in $2.2 million over Q3. So we've got the resources to execute. We've got the talent to execute. And I think we have the market opportunity to provide the tailwinds that we need.

So again, thank you, everybody, for joining us today. Look forward to being with you next time.

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