OpenEvidence Raises $250 Million Series D at $12 Billion Valuation as "ChatGPT for Doctors" Doubles Value in Three Months While Handling 18 Million Monthly Consultations

OpenEvidence, the AI-powered medical research platform widely known as "ChatGPT for doctors," announced Wednesday it has closed a $250 million Series D funding round at a $12 billion valuation, doubling its worth from just three months earlier and marking one of healthcare AI's fastest valuation climbs on record. Thrive Capital and DST Global led the round, with participation from existing investors including Sequoia, Google Ventures, Nvidia, Kleiner Perkins, Blackstone, Mayo Clinic, and others.

The Miami-based startup has now raised approximately $700 million in total funding within just 12 months, starting from its February 2025 Series A round at a $1 billion valuation through Sequoia. The company's value reached $6 billion after a $210 million Series B in July before jumping to $12 billion in the latest round, representing a 12x valuation increase in under a year and establishing OpenEvidence as the most valuable healthcare AI company globally.

OpenEvidence's rapid valuation appreciation reflects explosive growth in clinical adoption and usage metrics. The platform supported approximately 18 million clinical consultations from verified U.S. physicians in December 2025 alone, up from roughly 3 million monthly consultations one year earlier—a sixfold increase demonstrating the platform's integration into routine medical practice.

CEO Daniel Nadler, who previously founded and sold AI company Kensho Technologies to Standard & Poor's for approximately $700 million in 2018, claims OpenEvidence is now used by more than 40% of physicians in the United States, making it the most widely adopted AI platform among American doctors. "OpenEvidence is effectively the default operating system of medical knowledge in the United States today," said Kareem Zaki, partner at Thrive Capital.

The company estimates that more than 100 million Americans were treated by a doctor using OpenEvidence last year, highlighting the platform's reach across the healthcare system. Unlike consumer AI tools trained on broad internet content, OpenEvidence trains exclusively on peer-reviewed medical journals and clinical data, providing citation-linked answers synthesized from trusted medical literature.

OpenEvidence positioned itself strategically by striking official AI partnerships with leading medical publishers including the New England Journal of Medicine, the American Medical Association, the National Comprehensive Cancer Network, and the American College of Cardiology. This unique access enables the platform to answer physicians' questions using content directly from authoritative medical sources, increasing accuracy and physician trust compared to general-purpose AI systems.

"If a doctor tried to stay current by reading only the new evidence in the top 10 medical journals and only the most recent changes to their specialty guidelines, it would take nine hours of their day, each day," Nadler explained. "Without a technology like OpenEvidence, doctors may miss critical new findings or guidelines simply because they lack the time to find them."

The platform's multi-AI agentic architecture routes physician questions to specialized medical systems optimized for different clinical tasks. An independent study showed OpenEvidence is used by more American physicians than all other AI tools for physicians combined, according to the company, though it did not disclose the study's methodology or sponsorship.

OpenEvidence crossed $100 million in annualized revenue last year, primarily through an advertising-based business model that allows free access for any clinician with a national provider identifier number. Companies pay for video ad placements shown to physicians within the OpenEvidence app, enabling rapid adoption without subscription barriers that might limit reach in small practices lacking IT budgets.

Nadler says 95% of new users hear about OpenEvidence from another physician, driving organic growth through word-of-mouth referrals. "Most health care in America isn't happening at billion-dollar hospitals in New York or San Francisco," Nadler noted. "It's happening in small practices that don't have IT departments or budgets for expensive software."

The advertising approach represents an unconventional monetization strategy in enterprise AI but aligns with consumer technology business models. Last week, OpenAI announced it was testing an ad-supported version of ChatGPT, suggesting industry movement toward advertising as AI companies seek sustainable revenue beyond subscriptions.

The massive funding round comes as competition in healthcare AI intensifies. OpenAI launched "ChatGPT Health" earlier this month, while Anthropic released "Claude Healthcare"—both HIPAA-compliant extensions of their consumer chatbots designed for medical applications. These moves by foundation model companies signal growing recognition of healthcare's revenue potential as a sector representing nearly 20% of U.S. GDP with $5 trillion in annual spending.

Despite emerging competition, Nadler argues OpenEvidence maintains advantages through physician focus, data quality, and first-mover benefits. "We've already gathered hundreds of millions of real-world clinical consultations from verified physicians—that feedback loop is incredibly hard to replicate," he stated. "Even if someone copied the playbook today, they'd still be far behind because it's not just the partnerships, it's the real-world usage data."

The company has begun expanding beyond clinical question-answering. In August, OpenEvidence launched a tool enabling doctors to create medical notes enriched with external healthcare data, broadening its utility within physician workflows beyond literature search.

When asked about IPO prospects, Nadler suggested healthcare AI application companies will follow foundation model companies to public markets. "There's an order to nature," he said. "Foundation model companies go public first. Then the application layer follows." OpenAI, Anthropic, and SpaceX have all been rumored as potential 2026 IPO candidates.

A Silicon Valley Bank report released earlier in January raised questions about whether companies like OpenEvidence can deliver on stratospheric valuations through advertising and software-as-a-service business models alone, suggesting the company may eventually "tap the value of the data they're already collecting" to offer additional services to pharmaceutical companies or other healthcare customers.

For now, OpenEvidence plans to invest the new capital heavily in research and development and compute costs associated with its multi-AI agentic architecture, which the company claims provides the highest quality and most accurate medical answers available. The rapid scaling of both usage and valuation positions OpenEvidence as a test case for whether vertical AI applications can sustain billion-dollar valuations and challenge general-purpose foundation models in specialized domains.