OpenEvidence’s rapid ascent from an obscure health-tech startup to a $12 billion company in under a year is becoming one of the clearest signals that artificial intelligence in medicine has moved beyond experimentation and into the heart of the U.S. health-care system.
The Miami-based company, often described as “ChatGPT for doctors,” said it has closed a $250 million funding round led by Thrive Capital and DST, pushing its valuation to $12 billion. The deal caps a remarkable run. In February, OpenEvidence raised $75 million from Sequoia at a $1 billion valuation. By October, that figure had surged to $6 billion. In total, the company has now raised about $700 million from investors that include Google’s venture arm, Nvidia, Kleiner Perkins, Craft Ventures, and Mayo Clinic.
The speed of the re-rating underscores both investor appetite for applied AI and the belief that health care may offer one of the largest and most defensible markets for the technology. Health spending in the U.S. now runs at roughly $5 trillion a year, close to 20% of gross domestic product, making it the single largest slice of the real economy. For venture capital, it represents a rare combination of scale, urgency, and long-term demand.
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OpenEvidence was founded in 2022 by Daniel Nadler, who previously built Kensho Technologies, an AI firm acquired by Standard & Poor’s for about $700 million, and Zachary Ziegler, a Harvard PhD student specializing in artificial intelligence. Nadler’s track record has helped reassure investors wary of flashy AI startups with limited execution experience.
At its core, OpenEvidence offers a clinical decision-support chatbot designed specifically for physicians. Nadler rejects the idea that it is simply a medical-flavored version of a consumer chatbot. He says the system is trained on peer-reviewed scientific journals and trusted medical sources, not the open internet or social media, which he argues can introduce noise and low-quality information into high-stakes clinical settings.
“‘ChatGPT for doctors’ is a useful shorthand,” Nadler said, “but what we really do is help physicians make high-stakes clinical decisions at the point of care.”
That positioning matters as regulators, hospital systems, and clinicians remain cautious about AI tools that hallucinate or lack transparency. By narrowing its focus to verified physicians and curated medical data, OpenEvidence is trying to sidestep some of the reputational and legal risks that hang over more general-purpose models.
Nadler claims the strategy is working. He said more than 40% of U.S. physicians now use OpenEvidence, a figure that, if accurate, would make it one of the most widely adopted AI platforms in American medicine. The company says it topped $100 million in annualized revenue last year, driven largely by organic growth. According to Nadler, 95% of new users discover the platform through other doctors, a word-of-mouth dynamic that is rare in enterprise software and difficult for rivals to replicate.
The growth story is also tied to OpenEvidence’s unconventional business model. Unlike many health-tech startups that rely on expensive subscriptions sold to hospital systems, OpenEvidence leans heavily on advertising. Companies can pay for video promotions inside the app, allowing the core product to remain free for physicians.
Nadler argues this approach lowers barriers to adoption, especially for small practices that lack IT departments or budgets for enterprise software.
“Most health care in America isn’t happening at billion-dollar hospitals,” he said. “It’s happening in small practices.”
The ad-based model places OpenEvidence at the leading edge of a broader shift in AI monetization. For much of the past two years, leading AI companies have relied on subscriptions or enterprise contracts while absorbing heavy losses. That stance is beginning to soften. OpenAI said last week it is testing an ad-supported version of ChatGPT, an acknowledgment that advertising may be one of the few ways to support mass-market AI use without passing costs directly to users.
Nadler has been explicit about wanting to avoid the capital-burning strategies embraced by some rivals. He said OpenEvidence is trying to balance rapid growth with a credible path to profitability, distancing himself from startups that are “openly planning to burn billions or tens of billions” in pursuit of scale. The comment reads as an implicit contrast with foundation model developers whose infrastructure costs continue to balloon.
Competition, however, is intensifying. OpenAI recently launched ChatGPT Health, while Anthropic is pushing Claude Healthcare. Both products are HIPAA-compliant extensions of popular consumer chatbots, backed by companies with far deeper resources than OpenEvidence. Nadler insists his company’s moat lies in its physician-first focus, data quality, and early lead.
“We’ve already gathered hundreds of millions of real-world clinical consultations from verified physicians,” he said, describing a feedback loop that continually improves the product and is hard to reproduce quickly.
The claim highlights a broader truth about AI applications: once embedded in daily workflows, switching costs rise sharply.
The funding round also lands against a backdrop of renewed momentum in AI investing. According to CB Insights, there were six AI funding rounds exceeding $1 billion in the third quarter of last year alone. Anthropic is reportedly in talks to raise another $10 billion, while Elon Musk’s xAI announced a $20 billion round this month. For investors, OpenEvidence sits at the intersection of this capital surge and a sector long seen as ripe for technological overhaul.
Despite takeover interest from large tech companies eager to bolster their health-care offerings, Nadler says he intends to keep OpenEvidence independent. Having gone through an acquisition with Kensho, he said this time he wants to build a company that compounds over many years rather than exiting early.
On the question of an initial public offering, Nadler was blunt. He believes application-layer companies like OpenEvidence will have to wait until foundation model developers such as OpenAI and Anthropic go public first, following what he described as the natural order established during the early internet era.
OpenEvidence’s latest round cements its status as one of the most closely watched AI health-care startups. It is believed to be a confirmation that AI’s push into medicine is no longer speculative, and OpenEvidence has placed itself squarely at the center of that transformation.