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 datasets 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…
Snorkel AI, a startup that helps AI labs and corporations build training datasets 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 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. 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 billion milestone 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. Topics AI, data labeling, Fundraising, snorkel ai, Startups When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence. Marina Temkin Reporter, Venture Marina Temkin is a venture capital and startups reporter at TechCrunch. Prior to joining TechCrunch, she wrote about VC for PitchBook and Venture Capital Journal. Earlier in her career, Marina was a financial analyst and earned a CFA charterholder designation. You can contact or verify outreach from Marina by emailing marina.temkin@techcrunch.com or via encrypted message at +1 347-683-3909 on Signal. View Bio October 13 – 15 San Francisco Your next big connection is at Disrupt.Connect with 10,000+ founders, VCs, operators, and tech leaders. Explore tomorrow’s breakthroughs, hear what’s shaping tech today, and save up to $200 by Sept. 25 at 11:59 p.m. PT. BOOK NOW Most Popular Meta’s Muse is outpacing ChatGPT’s early mobile launch Sarah Perez Tilly Norwood’s press tour is going about as well as you’d expect for an AI Amanda Silberling Anthropic is operating a lab that conducts biology experiments Julie Bort A new kind of AI model from a ChatGPT inventor is thrilling developers Tim Fernholz Google’s new ‘CC’ is an AI agent that helps families run their households Sarah Perez OpenAI caught its models leaving notes to successors to hide bad behavior Rebecca Bellan Microsoft exec called AI scraping ‘the largest theft of labor in human history,’ new unredacted filings reveal Rebecca BellanSource: TechCrunch — Published — Category: Business