The Pulse
Snorkel AI raises $350M at a $3.5B valuation
Snorkel AI has raised $350 million in a Series E round that values the company at $3.5 billion. The Stanford spinout says its annualized revenue run-rate has exceeded $375 million as customers demand specialized training data, evaluations a
AI.info Team ·
Snorkel AI says its annualized revenue run-rate has passed $375 million, an increase of more than 18 times in less than a year. The company is using that growth to support a $350 million Series E financing round that values the Stanford spinout at $3.5 billion.
Insight Partners and S32 co-led the round, according to Snorkel’s September 22 announcement. Existing investors including Addition, Greylock, Lightspeed, GV, Factory, Prosperity7, Walden Catalyst and Wells Fargo also participated, alongside new backers such as March Capital, Blumberg Capital, Allegis Capital, Frontline, Standard and Third Point Ventures. Snorkel AI’s announcement says the financing will expand its data factory and research work.
From labeling software to finished AI data
Snorkel began as a software company focused on data-labeling automation after emerging from research at the Stanford AI Lab. The company now sells completed datasets, benchmarks, evaluations and reinforcement-learning environments to AI labs and enterprises. TechCrunch reported that the new valuation is nearly three times the $1.3 billion value assigned to Snorkel’s $100 million Series D round 17 months ago.
The shift reflects a change in what customers are buying. Instead of paying only for tools that help teams label examples, customers increasingly want finished data products and simulated tasks that can train or test advanced systems. Snorkel says its Data-as-a-Service offering launched in September 2025 and drove the sharp increase in revenue.
“The teams pushing the frontier want a research data partner who pioneers the science of data development,” Alex Ratner, Snorkel AI’s co-founder and chief executive, said in the company’s announcement. “That’s what Snorkel was built to be: the frontier lab for agentic data, combining human excellence with over a decade of research and technology.”
Why specialized data commands new funding
Snorkel describes its work as “Data 2.0,” a category built around expert-designed tasks, evaluation environments and grading rubrics rather than simple labeling exercises. Those materials can take qualified specialists hours or days to design, particularly when they are intended to test coding, legal reasoning, medical knowledge or the behavior of AI agents.
The company combines subject-matter expertise with software and AI models that generate data and perform quality checks. That hybrid approach separates Snorkel from a basic labor marketplace: the product is the completed dataset or environment, not an hourly pool of annotators.
Snorkel says its work supports training and evaluation for leading AI labs and enterprises, although its announcement does not identify individual customers. The company’s research roots remain part of its pitch. Snorkel says its founding team has contributed to more than 250 peer-reviewed papers that have received more than 25,000 citations.
Investors back a broader data business
The new round places Snorkel among a group of heavily funded companies selling access to expert-generated AI data. Reuters reported that Snorkel’s annualized revenue run-rate had risen from roughly $20 million a year earlier, while the company’s own announcement gives the latest figure as more than $375 million. Those figures are run-rate measures rather than audited annual revenue.
“Snorkel’s research-grade approach to AI data, environments, and measurement is becoming an increasingly important ingredient in building capable and reliable AI systems,” Lonne Jaffe, managing director at Insight Partners, said in the company release. He said the firm was backing Snorkel’s work in healthcare, law and software engineering.
Andy Harrison, CEO and general partner at S32, said Snorkel’s expert-designed environments create a connection between human expertise and AI systems. The company plans to spend the new capital expanding its data factory, investing in enterprise and industry-specific AI work, extending research into new data types and supporting open research programs such as its Open Benchmarks Grants initiative.
The valuation rests on execution after the raise
Snorkel’s financing arrives as AI developers spend more on the data needed to train and evaluate systems that operate across longer, more complicated tasks. The company’s challenge is to turn demand for specialized datasets into repeatable products while maintaining the expert input that gives those products value.
The $3.5 billion valuation also sets a demanding commercial benchmark. Snorkel has disclosed rapid run-rate growth and a clear change in business model, but the September 22 announcement does not provide audited financial statements or name the customers behind the reported revenue. The immediate test is whether the company can scale its research-heavy data operation without reducing the quality that persuaded investors to fund it.