Snorkel AI triples valuation to $3.5B as training-data demand surges

The round was led by Insight Partners and S32 and values the seven-year-old startup at nearly triple the $1.3 billion valuation it garnered when it raised $100 million in a Series D 17 months ago. Existing investors, including Addition, Lightspeed, Greylock, GV, and Wells Fargo, also participated. While Snorkel originally provided software for data-labeling automation, it shifted last year to providing customers with completed datasets — an offering it calls data-as-a-service. Rather than operating purely as a human-expert marketplace, Snorkel relies on a hybrid approach, using its software and models to generate data synthetically alongside subject-matter experts.

Snorkel says its current annualized revenue run rate now stands at $375 million, an eighteenfold increase over the last 12 months, fueled by AI labs’ appetite for high-end training data. Other data companies positioning themselves as AI data labs have seen similar growth: Mercor’s gross annualized revenue has climbed to $2 billion, Handshake hit the $1 billion milestone earlier this year, and Micro1 has scaled to $500 million, according to TechCrunch reporting. Since these companies typically pay out roughly 60% to 70% of their top-line income directly to the domain specialists doing the work, their actual net annual revenue is substantially lower than those headline gross figures.

Because Snorkel sells reinforcement learning (RL) environments and complete datasets rather than human labor, the company says payments to its human experts are accounted for in its cost of goods sold rather than in headline-generating annualized revenue numbers. Snorkel launched commercially in 2019 following four years of research by co-founder and CEO Alex Ratner and his team at a Stanford AI lab.

Why it matters

The nearly threefold valuation jump in under a year and a half signals how much investor money is chasing the infrastructure behind AI training, not just the models themselves.