The 'ChatGPT for doctors' — AI clinical decision support used by 40% of US physicians
HQ: Miami, FL, United States | Founded: 2022 | Employees: ~200 (2026, est.) | Stage: Late Stage VC ($12B valuation) | Website: https://www.openevidence.com
OpenEvidence was founded in 2022 by Daniel Nadler, the founder and former CEO of Kensho, the AI analytics company acquired by S&P Global for $550M in 2018. Nadler's insight: doctors don't need a chatbot — they need an AI that reads the medical literature and answers clinical questions with sources they can trust. OpenEvidence's engine synthesizes evidence from peer-reviewed journals and clinical guidelines, giving clinicians answers with citations — designed for the stakes of real patient care rather than general-purpose chit-chat.\n\nThe product spread entirely through physician word-of-mouth. OpenEvidence offered its core product free to verified clinicians and monetized through a separate advertising platform (pharma marketing reaching physicians at the point of care). The result was historic adoption: within three years, roughly 40% of US physicians were using the product, with ~20 million clinical consultations per month-and-counting and claims to be the fastest-growing physician application in history. The model was validated financially in parallel: $100M+ revenue in 2025, ~$150M annualized by end of 2025, and ~$300M by July 2026 (Sacra).\n\nCapital followed: more than $300M raised by mid-2025 (including a $210M round at a $3.5B valuation in July 2025), a $200M Series C at $6B (October 2025), and a $250M round in January 2026 that doubled the valuation to $12B — with SoftBank among the backers. Nadler retains a roughly 60% stake, and the company moved its HQ to Miami, cementing its status as the flagship of the clinical-AI category and one of the fastest-growing companies in healthcare technology.
OpenEvidence cracked the hardest distribution problem in healthcare AI: getting doctors to actually use it. By offering a genuinely evidence-grounded assistant free to clinicians (monetized via pharma advertising), it achieved what no other clinical AI has — ~40% of US physicians using the product, ~20 million clinical consultations, and the fastest adoption of any physician application in history. The numbers followed: $100M+ revenue in 2025, $300M annualized by July 2026, and a valuation that doubled from $6B to $12B in three months (January 2026). The bull case is the bottom-up doctor-first flywheel — every physician using it makes the evidence base and brand stronger; the bear case is advertising-driven monetization in a regulated industry, the clinical-liability question at the center of every medical AI, and well-funded rivals (Epic, Google, Microsoft/Nuance) with distribution of their own.
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