Miami does not usually whisper when it decides to speak. OpenEvidence is no exception. The AI medical search company quietly announced a $250M Series D that doubled its valuation to $12B, and the...
Miami does not usually whisper when it decides to speak. OpenEvidence is no exception. The AI medical search company quietly announced a $250M Series D that doubled its valuation to $12B, and the silence around it said more than the noise most rounds try to make. When 40% of licensed U.S. physicians already use your product, you do not need theatrics. You let the evidence talk.
OpenEvidence was founded in October 2021 by Daniel Nadler and Zachary Ziegler to solve a problem every doctor knows and every system pretends is manageable. Medical knowledge now doubles every five years. Human recall does not. OpenEvidence stepped into that gap with a clinical search engine trained only on peer reviewed medicine, not internet soup, not vibes, not half remembered abstracts. What it delivers is synthesis with citations, answers that show their work, and speed that fits into a real exam room, not a demo slide.
The traction is not theoretical. More than 430,000 verified physicians across over 10,000 hospitals use OpenEvidence. 18M clinical consultations ran through the platform in December 2025 alone. Over 100M Americans were treated last year by doctors using it at the point of care. Adoption spreads almost entirely by word of mouth, which in medicine is the hardest referral economy in the world. Doctors do not recommend tools that waste time or get things wrong.
This Series D was co-led by Thrive Capital and DST Global, with continued backing from Google Ventures and Nvidia. It follows a valuation climb from $1B in February 2025 to $12B less than a year later. That pace does not come from pitch decks. It comes from daily clinical dependency. When physicians trust a system during real decisions, capital tends to follow without much persuasion.
Under the hood, OpenEvidence runs a multi model architecture that routes each question to the right specialist AI, mirroring how care teams actually work. 35M peer reviewed articles. One hundred sixty specialties. Integrated guidelines from NCCN, ACC, AMA, and others. Features like DeepConsult and OpenEvidence Visits are designed to think while clinicians move, not after hours when mistakes get made.
Daniel Nadler brings scars from building Kensho and a personal reason rooted in medical error. Zachary Ziegler brings the research depth to make ambition behave. Travis Zack grounds it in clinical reality. Together they built something rare in AI right now, a product that physicians use not because it is impressive, but because it is useful.