Data 2.0 and the research era of AI data

Today, I’m excited to announce Snorkel’s $350M Series E financing at a $3.5B valuation, led by Insight and S32, with participation from Third Point, March, Blumberg, Allegis, Standard VC, Frontline, and existing investors Addition, Lightspeed, Greylock, GV, P7, Wells Fargo, Walden Catalyst Ventures, and Factory. Since launching our new data-as-a-service offering nearly a year ago, we’ve grown over 18x, and this week crossed an annualized revenue run rate of $375M. We’re honored to now partner with the leading frontier labs, hyperscalers, neolabs, vertical AI leaders, enterprises, and U.S. government agencies who view data as one of the most important ingredients for safe and effective AI. We started Snorkel as a research project a decade ago at Stanford. Our thesis was simple: AI progress would become increasingly data-centric – and therefore data development should be studied as a true research and technology problem, not just a staffing and crowdsourcing one. Today, as AI capabilities verge on superhuman, building the data and environments to safely measure and train AI is becoming too hard for even the smartest human experts to do alone. Only humans and AI agents, collaborating together in compounding ways, can meet the accelerating needs of the frontier and keep…