For months, Kleiner Perkins partner Aditya Naganath had been mulling over his investing thesis that the next wave of AI wasn’t going to be a chatbot—it was going to be software that does the work autonomously, for hours at a time, across thousands of tasks at once. The trouble was, nobody had built the plumbing for it yet. Then he met Neil Movva.
“It felt obvious to both of us that you’re going to need a different, specific inference platform built for these long-running agents,” Naganath told Fortune.
Now, six months after Naganath and Movva first chatted, Movva’s startup, Sail Research, has launched from stealth with $80 million in seed and Series A funding at a $450 million valuation, Fortune learned exclusively. Kleiner Perkins led the Series A. Sequoia, Redpoint, Theory Ventures, Vine Ventures, and CRV also participated.
Sail Research wants to fix one of AI’s expensive problems. AI infrastructure was designed for quick, single exchanges—think a chatbot answering a question. But enterprises are increasingly deploying AI agents that run autonomously for hours, reading entire codebases, screening hundreds of job candidates, or researching complex topics without a human in the loop. At that scale, enterprise AI bills have tripled even as per-token prices have fallen, because agentic workflows consume tokens at a rate 50 to 500 times higher than simple chat. Goldman Sachs forecasts a 24-fold increase in token consumption by 2030.
