The round values the company—dubbed the “ChatGPT for doctors”—at $12 billion, company officials told CNBC Wednesday (Jan. 21).
OpenEvidence, founded in 2022, offers a chatbot for doctors, with AI models trained on data from leading scientific journals, Founder Daniel Nadler said in an interview with CNBC.
“‘ChatGPT for doctors’ is a useful shorthand, but what we really do is help physicians make high-stakes clinical decisions at the point of care,” he said. “It’s not trained on the open internet or social media, which can introduce low-quality medical information.”
He added that the company is the most widely used AI platform by doctors in the U.S., with upwards of 40% of physicians employing the tool. He pointed to the vast opportunity in health care, which accounts for close to 20% of gross domestic product in the U.S. with $5 trillion in annual spending.
“Health care is the largest segment of the real economy,” Nadler said. “People realize there could be a lot of winners in the space.”
The report noted that those winners could include AI giants like OpenAI and Anthropic, both of which have recently launched health products. And as covered here Wednesday, OpenAI argues that healthcare could be one of the fields that helps drive wider adoption of its tech.
OpenEvidence raised $210 million in a round last summer, PYMNTS reported.
Meanwhile, PYMNTS wrote last week about AI’s role as a “key accelerant” in the world of healthcare procurement.
“Healthcare systems generate enormous volumes of procurement data, but historically, they’ve used very little of it,” that report said. “Spreadsheets and static forecasts ruled the day, even as supply environments grew more volatile. Legacy systems, regulatory complexity and cultural inertia remain endemic bottlenecks to progress.”
But as procurement decisions directly impact cash flow, operating margins and clinical performance, the path for healthcare’s B2B supply chains is one of modernization.
Inventory, the report added, has always been “healthcare’s necessary evil.” Too much freezes capital and expires on the shelf. Too little can cause clinical risk and operational chaos. Many procurement organizations try to ease that tension by overbuying and “hoping for the best,” though AI is helping bring an end to those compromises, PYMNTS added.
“By continuously learning from real consumption, modern procurement platforms recommend where inventory buffers actually matter and where they don’t. High-risk, life-critical items get priority. Predictable supplies move closer to just-in-time replenishment.”
