As AI emerges as the greatest secular technology theme since the Internet in the ‘90s, there is a LOT of hype and hyperbole surrounding AI Companies. While mega-cap names like nVidia, Google, and Microsoft dominate the AI Investment Landscape, it also makes sense to pay attention to some of the smaller Picks n Shovel plays in the AI Arena. One such company is Innodata Inc. (INOD).
Innodata is a Data-Engineering Provider, specializing in Generative AI Foundational Model Development. Founded in 1988, Innodata has 30+ years of experience in the Data-Engineering field and offers a full array of Services and Platforms for the Builders and Adopters of Generative AI.
Innodata’s early start in the field has given the company first-mover advantage but it is the decades of experience and expertise with Data Engineering which sets the quality of its data apart from its competitors.
On the most recent Q1 Conference Call, Mgmt summed up its “edge” in the field and why one of the company’s largest customers calls Innodata its “Secret Weapon.”
For Big Tech customers, we provide a broad range of services to support their Generative AI Programs. This includes creating Instruction Datasets, which you can think of as the programming behind Large Language Models.
One of our large Big Tech customers stated that the quality of these Instruction Datasets has an outsized influence on the performance of their models, and that some of their biggest improvements in model quality come from carefully crafted instruction data sets…
As the Generative AI Gold Rush begins to take off in force over the next decade, there are going to be some fabulous, untold winners in the space. But as they teach in Business School, often times “the best way to win the Competition is to stay out of it.” And there is enormous opportunity in “staying out”.
Leaps and Bounds don’t even come close to describing the growth occurring in the Generative AI Market over the coming decade. Like AI itself, it’s difficult to conceptualize what is happening. The market is projected to grow from $40B in 2022 to $1.3T by 2032 (+42% CAGR).
What’s even more impressive is that the expected growth rate for Innodata’s specific focus-market – Generative AI IT-Focused Services – is projected at 100% CAGR through 2032. Clearly, Mgmt has been sharpening their skates for the past few decades and have skated to exactly where the puck is going be. Please take a look:
On May 7, Innodata reported very illuminating Q1 Numbers and Highlights.
Not only did the company report a monster jump in Adj EBITDA but Mgmt also raised its FY24 Guidance to $121.5M (40%+ YoY) “due to accelerating business momentum” with the additional assurance that the 40% projected growth is “still a reasonably conservative target.” Indeed, the tone and commentary on the Conference Call was what every Growth Investor wishes to hear.
We also signed two additional Big Tech companies… As a result of these new wins, we now serve seven Big Tech customers. We believe we will continue to grow with these customer relationships in 2024, and that we may grow some of them, possibly quite substantially.
One of our large Big Tech customers stated that the quality of these instruction data sets has an outsized influence on the performance of their models… This statement crystallizes why we have become the partner of choice for such customers.
It is evident that Big Tech’s aspirations extend beyond today’s predominantly text-to-text English language models... All of these dimensions will require modeling with the kind of data that we create. We believe we are still in the early innings of this journey.
We believe that Enterprise Adoption is about to enter a Cambrian Period of explosive growth as a result primarily of three technology developments now underway.
The thesis for Innodata is two-fold. First off, Innodata has positioned itself in the sweet-spot of the Big Tech Secular AI Spend which, as Mgmt attests, is “still in the Early Innings of the journey.”
INOD now serves 7 Big Tech Companies, all which are spending significantly on AI, and Mgmt believes “we have an opportunity to scale with ALL of them.” Given what we do know about the AI Market Opportunity, we believe Innodata should win additional add-on contracts with these Hyperscalers, meaning there is more upside to its numbers going forward.
Secondly, we believe the Enterprise Market represents the next layer of explosive growth for Innodata in 2025 and beyond. (Reread the final bullet point above please!) On the Call, Mgmt discussed how “three technological developments” will transform Enterprise usage of Generative AI in the next few years. They foresee Generative AI moving from its current Level-Zero iteration – ChatGPT in its standalone form – to an incredibly powerful, highly-complex Level-Three System, where costs come down dramatically “making it possible for Enterprises to train and serve models at scale.”
Innodata envisions a Level-Three System which is able to handle multiple queries and consider the context of the conditions as well. To get a sense of the complexity, Mgmt provided an example of an AI-Enhanced Virtual Innodata Agent for employees:
An Innodata employee might ask a virtual Innodata agent: please look up how many days off Innodata employees get, check how many days off I have left, and request a week off around my son’s graduation, so long as there are still available hotels in Boston.
The belief is that as the AI sophistication scales and costs come down Enterprise adoption will increase exponentially. Innodata intends to be there every step of the way.
We intend Innodata to offer Enterprise all of the services they require to navigate the journey from Level-Zero to Level-Three and beyond. This will include custom development, integration and fine tuning services, as well as managed services around data readiness and data governance and industry specific workflow platforms. We are not alone in thinking the Enterprise Market for Generative AI is about to explode.
Taken all together, for FY24, instead of the current guide for Revenue of $121.5M, we see $125-$130M. Looking further ahead, with the Enterprise Adoption kicking in 2H of FY25, another year of 30% Top Line growth to $165M seems well-achievable. Furthermore, Bottom Line leverage will kick in during FY25, leading to strong incremental drop-down, along with Margin Improvement and Triple-Digit Earnings.
INOD currently trades for just under 3x Sales. At 3x FY25 Sales of $165M, you get 50% upside, $16-17PT. If the Market becomes enamored w AI Names again, the P/S could be re-rated even higher.
Innodata has a bulky client base. If they should lose one of their Big 7 Tech Companies or not scale with them as rigorously as anticipated, this would negatively affect guidance and our thesis. There is also the risk that one of the Big 7 could elect to bring their Data Engineering needs in-house but, given it is early days for AI Adoption, we don’t think this poses much risk in the near-term.
Finally, we expect CapEx to trend higher as Innodata invests in New Hires and Sales & Marketing. While Margins might get clipped in the short-term, the company is ultimately targeting Gross Margins of 40% as they hit their run-rate stride. Keep in mind that these investments are for all the right reasons, as Mgmt expects a significant increase in Revenues this year.
Our plan with INOD is to buy a small position at current levels and look to add on pullbacks to the upward-rising 10day EMA. There is meaningful Resistance between $11.80-$12.45 on the chart. If the price-action should surge through this level, we will fill out our position there.
STOP LOSS: 200day SMA / $8.65.
We like INOD and have a lot of faith in the Secular AI Opportunity, but it is not a trade we expect to go into overdrive immediately. Also, with Customer Concentration-Risk high (not a short-term risk, but one for 2025 and beyond), this also means our INOD allocation will be much lighter than a Conviction Level 10 name.
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Disclosure: We are long INOD stock. We may change our positioning at a moment’s notice, without notifying you of any such moves.
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