Snorkel AI triples valuation to $3.5B as demand for AI training data booms

Snorkel AI, a startup that helps AI labs and corporations build training data sets and simulated environments, has raised a $350 million Series E at a $3.5 billion valuation. The new round, which was led by Insight Partners and S32, valued 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 in the round. While Snorkel originally provided software fordata labeling automation, it shifted last year to providing customers with completed data sets, 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 18-fold increase over the last 12 months. That growth is fueled by AI labs’ insatiable appetite for high-end training data. Other data companies positioning themselves as AI data labs have seen a similar explosion in growth. Mercor’s gross annualized revenue has climbed to$2 billion, Handshake hit the$1 billionmilestone earlier this year, and TechCrunch reported that Micro1 has scaled to$500 million. Since these companies pay out roughly 60% to 70% of their top-line income directly to the domain specialists doing the work, it’s important to note that their actual net annual revenue is substantially lower than those headline gross figures. Given that Snorkel sells reinforcement learning (RL) environments and complete datasets rather than human labor, payments to its human experts are accounted for in its cost of goods sold rather than headline-generating annualized revenue numbers, according to the company. 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.