Snorkel AI has raised $350 million in a Series E round that nearly triples its valuation to $3.5 billion, the latest sign that investors are betting heavily on the infrastructure feeding large language models rather than the models themselves.
Insight Partners and S32 led the round, with participation from existing backers including Lightspeed, Greylock, GV and Wells Fargo, according to the company's announcement. The new valuation compares with $1.3 billion just 17 months earlier, and comes as Snorkel's annualized revenue run rate reached $375 million — an eighteenfold increase over the past year, according to TechCrunch.
From Labeling Software to Data-as-a-Service
Founded in 2019 by researchers who spun the company out of Stanford's AI lab, Snorkel initially sold software that automated the labeling of training data for machine-learning models. It has since shifted toward selling finished datasets and reinforcement-learning environments directly to AI labs and enterprise customers, a data-as-a-service model the company launched in September 2025 that blends synthetic data generation with human subject-matter experts.
The teams pushing the frontier want a research data partner who pioneers the science of data development.
Alex Ratner, co-founder and chief executive, Snorkel AI
Insight Partners managing director Lonne Jaffe said the firm backed the round because Snorkel's "research-grade approach to AI data is becoming increasingly important in building capable and reliable AI systems." The company said it would use the funding to expand capacity at its data factory, deepen investment in vertical and enterprise AI products, and extend its research into new data domains and modalities.
The round reflects a broader scramble among venture investors to fund the less-visible layers beneath frontier AI models — training data, evaluation and reinforcement-learning environments — as foundation-model developers compete for higher-quality, harder-to-obtain data sets. Snorkel's jump from a $1.3 billion to a $3.5 billion valuation in under a year and a half illustrates how quickly capital has moved into that niche, even as some investors privately question whether demand for specialized data services can keep pace with the sums now being committed to it.
The round drew a wide bench of backers beyond its lead investors, including March Capital, Blumberg Capital, Allegis Capital, Third Point Ventures and Prosperity7, according to the company's announcement, alongside earlier investors Addition and Factory. The breadth of the investor list underscores how far the fundraising environment for AI-adjacent infrastructure has broadened beyond the handful of megafunds that dominated headlines earlier in the boom.
