Barron’s: Google partner Innodata surged 11x in 3 years, is 'just getting started'

Barron's writes that investors should buy shares of Innodata, a small-cap provider of data solutions for developing generative AI models. The company’s stock has surged more than 11-fold over the last three years, yet things are “just getting started,” the publication believes. With AI adoption accelerating, companies are in growing need of high-quality data sets.

"For investors confident that we’re still in the early innings of the AI revolution, Innodata stock is a high-quality small cap to buy and hold for the long run," Barron's argues.

The real "secret sauce" behind AI progress is not the chips or algorithms on which the models run, but the quality of the raw data used to train them.

That is the message from Innodata, a company offering software that transforms raw data such as text, images, video, and sensor information into high-quality, AI-ready data sets. This work is increasingly important as developers build more-complex and sophisticated models, writes Barron's.

Innodata’s financial performance "tells the story," in the Barron's words. In the past three years, revenue has tripled, accompanied by a surge in profitability. In the second quarter, Innodata’s top line reached $58.4 million, up 79% year over year, while the gross margin expanded 10 percentage points to 39%.

The company’s stock has notched a "spectacular" 11-fold increase over the period thanks to healthy financial performance. Indeed, "despite the large gains, there’s a sense that Innodata’s growth is just getting started," Barron's wrote. Unlike other small-cap AI disruptors like C3.ai or BigBear.ai, which are struggling to reach profitability, Innodata is not only making money but also sports a clean balance sheet, with zero debt and growing free cash flow.  

The stock now trades 36% off the high reached on February 26, even taking into account the September 4 single-day surge of 12% to $41.10 per share. Following the sharp correction from highs earlier this year, the stock looks like a good bet for investors ahead of a rebound, Barron's reckons. Its forward P/E ratio of 30 looks attractive, especially in view of the company’s growth trajectory.

A risk for investors, Barron's points out, is that Innodata's two largest customers contributed more than half of total revenue over the past year. The company is addressing this by targeting expanded AI applications and what it sees as the future of the field: agentic AI.  

Maxim Group analyst Allen Klee pointed out in a recent research note, as quoted by Barron's, that emerging computing techniques and hardware optimization “should create greater demand for data training” as attention turns to the quality of data. Klee has a "buy" rating on the stock with a target price of $75 per share, implying more than 100% upside from the September 4 close.

In May, Wedbush listed Innodata as one of 30 tech companies that will be long-term AI winners, including Nvidia, Palantir, Microsoft, and Alphabet.

The stock currently has three “buy” ratings versus one “hold” from Wall Street analysts, MarketWatch data shows. The average target price of $66.75 per share implies upside of more than 62% versus the last closing price.

Innodata’s business began nearly 40 years ago with digitizing documents for clients. With the rise of e-books, the company moved into converting printed works into digital formats.

For a long time, Innodata was considered a slow-growth IT services and enterprise software provider. That changed in 2019, when the company switched its focus to high-quality data solutions for developing generative AI models.

This is how Barron's describe the core business idea: Innodata cleans up inaccurate, incomplete, or irrelevant data, combining a proprietary technology platform with over 6,000 expert consultants to annotate and validate information for various AI applications. This human-in-the-loop framework provides specialized services, such as fine-tuning and preference optimization to teach large language models to control their tone, avoid biases, and ultimately reduce errors. The company's partners include Google, Amazon, Microsoft, and Apple.

The AI translation of this story was reviewed by a human editor.