Venture capital has poured nearly $18 billion into healthcare AI in a single year. The return on that investment, by most accounts, is a smorgasbord of pilots. Roughly 83% of health systems are running generative AI experiments—and only 5 to 10% of those ever reach enterprise-wide deployment. The rest die in procurement, drown in integration reviews, or launch in two departments and quietly stop expanding.
UCSF Health, Kleiner Perkins, and Doerr Capital don’t think that’s purely a technology problem. They’re betting that the technology is being built in the wrong place.
The trio, Fortune learned exclusively, is launching UCSF Health Converge, a health AI accelerator built around a deliberately radical constraint: two to three companies a year, embedded inside UCSF’s actual clinical workflows, IT systems, and operational teams from day one. UCSF Health CEO Suresh Gunasekaran is blunt about what the program is pushing back against. “The vast majority of solutions, when they exit the accelerator and come to pitch us, are not ready to implement at the system level,” he told Fortune. “That final mile is missing.”
It’s a direct shot at an industry that has spent the better part of a decade building healthcare AI from the outside looking in. And UCSF isn’t the first to try a different approach. Mayo Clinic has run more than 70 startups through an accelerator program since 2022 that gives companies access to its patient data and expert feedback in exchange for a stake in the company. Cleveland Clinic struck a deal with Khosla Ventures last fall that lets the firm’s portfolio companies bring their products in and test them on real patients and providers. UCSF’s argument is that testing a product inside a hospital is fundamentally different from building it there.
Whether the model actually delivers is an open question, and the details Converge has put on the table so far don’t exactly answer it. There’s no disclosed equity structure—meaning it’s unclear whether UCSF gets an ownership stake in the companies it helps build—no stated program length, and no specific dollar commitment from Kleiner or Doerr. Gunasekaran described the terms as “flexible” and dependent on each company’s situation.
Kleiner, which raised $3.5 billion across two new funds in March with a heavy focus on AI, will decide whether to invest in Converge companies the same way it decides everything else—through its full six-person partnership. “It wouldn’t just be up to me,” Mamoon Hamid, partner at Kleiner Perkins, told Fortune.
John Doerr, whose personal vehicle Doerr Capital is co-anchoring the program alongside Kleiner, put the stakes in terms that are hard to dismiss: 100 million Americans currently have zero access to primary care, and the U.S. isn’t going to train its way out of that shortage. “We’re not going to be able to address that need by training and hiring more doctors,” Doerr told Fortune. “We’ve got to use AI to raise the license level at which everyone in our healthcare teams participates.”
He sees a historical parallel in Genentech—the biotech pioneer that was essentially born inside Kleiner Perkins’ offices in the 1970s, with scientists and investors building in the same room rather than across a procurement process. That proximity, he argued, is what made the biotech revolution real.
“We underestimated the challenge of changing human behavior—and by humans, I mean patients, caregivers, neurosurgeons,” he told Fortune. What AI changes, in his telling, is personalization at scale: the nudge that gets a patient to take their medication, the ambient note-taking system that sends a physician home to their family instead of their Epic charts.
