In the past year, OpenEvidence, an AI-powered medical search engine, has seen breakneck growth, rapidly expanding its reach with doctors.
OpenEvidence developed an AI-powered medical search engine and a generative AI chatbot exclusively for doctors that summarizes and simplifies evidence-based medical information.
In December alone, the company claims it supported about 18 million clinical consultations from verified physicians in the U.S., up from about 3 million consultations per month a year ago. OpenEvidence is now actively used daily, on average, by more than 40% of physicians in the U.S., spanning more than 10,000 hospitals and medical centers nationwide, according to the company.
The company asserts that 100 million Americans were treated by a doctor using OpenEvidence last year.
The health tech company banked $250 million in series D funding to invest heavily in the R&D and compute costs associated with its multi-AI agentic architecture. OpenEvidence will also use the funding to continue to build out its content licensing partnerships.
"The lion's share is training new models, training the next generation of digital intelligence, and compute costs," Daniel Nadler, founder and CEO of OpenEvidence, told Fierce Healthcare.
The series D round doubled its valuation to $12 billion, the company said. The company's valuation stood at $6 billion in October when it raised $200 million in series C funding—and that was just three months after it raised $210 million in a series B funding round in July.
OpenEvidence has raised roughly $700 million in the past year.
The Information reported the series D funding round back in December.
Thrive Capital and DST co-led the series D round. Previous investors include Sequoia, Google Ventures, Nvidia, Kleiner Perkins, Blackstone, Henry Kravis, Coatue, Conviction, ICONIQ, Greycroft, Breyer Capital, BOND, Craft Ventures, Goanna, Meritech, Alkeon, Mayo Clinic and others. Many of those investors also followed on in this round, executives said.
"OpenEvidence is effectively the default operating system of medical knowledge in the United States today,” said Kareem Zaki, partner at Thrive Capital, in a statement.
OpenEvidence, which is free to doctors and ad-supported, topped $100 million in annual revenue last year, according to executives.
During the J.P. Morgan Healthcare Conference in San Francisco last week, Nadler said the company was developing “medical super-intelligence” based on agentic artificial intelligence that is multimodal and multicloud.
Advances in agentic AI will enable a system of AI agents that can be subspecialists in clinical areas, he told investors and attendees during a packed session at JPM.
The company has strategically differentiated itself from other medical AI chatbots by being an early mover and a "copyright-friendly approach" to copyright holders, Nadler noted. OpenEvidence has collected tens of millions of clinical consultations and has inked content partnerships with medical journals that represent the gold standards of medical knowledge, Nadler noted in an interview back in July. OpenEvidence's AI models are trained only on medical journals and medical data.
OpenEvidence has formed strategic content partnerships with the American Medical Association, The New England Journal of Medicine, the Journal of the American Medical Association, and all 11 JAMA specialty journals, including JAMA Oncology and JAMA Neurology. The company also has partnerships with the American Academy of Family Physicians and the American College of Emergency Physicians.
Those content partnerships have helped to build trust with physicians, according to Nadler.
"The licensing partnerships early on were very critical. When there was the ChatGPT 'Big Bang' moment and doctors had their first exposure to a conversational interface, what we now call AI, which is basically a conversational interface with a computer, the doctors loved it. But, they wanted to use a tool that gave them that experience of a conversational interface, but where, when they were asking a question, the answer was grounded in the types of resources that they would typically use as doctors, as opposed to grounded in the open internet or grounded on something I read in social media or sources that could produce very low quality information," Nadler said.
"We were the first to market with an AI product for doctors where it was grounded in the sources and references that they actually had been using for years and decades," Nadler asserted. "We gave them the traditional content in a new interface."
In December, the company rolled out a new Dialer feature as a HIPAA-secure communication tool for clinicians.
A recent survey by Offcall, a company that provides salary and work transparency, along with financial education for doctors, found that 67% of doctors use AI tools daily in their practice and nearly 90% use AI at least weekly. According to that survey, OpenEvidence is the most widely used AI tool among doctors, with 45% of physicians using it—more than the other 9 AI tools combined.
OpenEvidence has now set its sights on building specialist AI models to evolve its platform. "The big realization we had, and I think all the big AI companies are coming to the same realization, is that the next generation of digital intelligence is not going to be a single model, no matter how big it is. It's going to resemble the way that human collective expertise works," he said.
At leading hospitals and academic medical centers, a team of specialists and subspecialists works together to care for patients, such as a team that is comprised of oncologists, pathologists and radiologists, he noted.
"Super intelligence would be something like a system that can solve hard medical cases faster than teams of experts all working on that medical case for years," Nadler said. This requires coordinating an orchestra of proprietary, medically-specialized AI models, each focused on a distinct clinical sub-specialty, much like the expert care teams in top hospitals. A central “conductor” AI routes each physician's question to the most relevant sub-specialist model, according to Nadler.
"We're in the first 2% of this wave because no one has scratched the surface of 'super intelligence'," Nadler said.
Nadler asserted that the first steps toward this future could be in oncology AI, pointing to OpenEvidence’s partnership with the National Comprehensive Cancer Network (NCCN). The two organizations announced a licensing agreement in November to make the NCCN’s oncology guidelines accessible through OpenEvidence’s medical AI tech.
OpenEvidence's growth comes as Anthropic and OpenAI increasingly target healthcare. In the past two weeks, Anthropic launched Claude for Healthcare, AI tools and resources purpose-built for providers and payers. OpenAI rolled out ChatGPT for Healthcare as a workspace for researchers, clinicians and administrators.
"I respect the hustle. Our view is that healthcare can't be a side hustle," Nadler said. "OpenAI has the unseat Google division, the unseat Apple division, the unseat Nvidia division and the unseat OpenEvidence division. We have one division. We wake up every morning thinking about healthcare. We go to sleep thinking about healthcare. A bet on OpenEvidence is a bet that focus wins."