Medical AI Startup OpenEvidence Weighs $200 Million Funding Round

Medical-focused artificial intelligence startup OpenEvidence has reportedly considered raising $200 million at a $20 billion valuation.

However, the company is unlikely to proceed, partly because the fundraise will dilute founders and shareholders, The Information reported Friday (July 17), citing a source involved in the discussions.

That source added that OpenEvidence has also held acquisition talks with a large tech company in the last few months.

The company is now generating around $300 million in annualized revenue , which implies close to $25 million in revenue each month, the source said. That’s double what OpenEvidence was bringing in roughly seven months ago, when it was in talks to raise at a $12 billion valuation, the report added.

According to the report, this growth could ease fears among investors that bigger AI labs, which are putting out competing apps, will absorb AI application startups. For example, OpenAI in April launched ChatGPT for Clinicians , which helps healthcare professionals with documentation and medical research.

OpenEvidence is running at breakeven on a cash flow basis, as it invests in training its models for duties like generating medical notes and searching information from medical journals, The Information’s source added.

As covered here in May, OpenEvidence’s AI-powered medical search engine is used by 860,000 licensed and verified U.S. clinicians. Among the company’s most recent offerings is Voice Mode, a hands-free feature that allows clinicians to ask questions and get spoken, evidence-based answers without touching a screen.

“When I’m in the ED, I’m never at a workstation when I actually need an answer,” Dr. Ania Bilski , vice president of clinical AI at OpenEvidence and a practicing emergency medicine physician at University of California, San Francisco and Kaiser Permanente , told Fierce Healthcare.

Meanwhile, recent PYMNTS Intelligence research shows that healthcare firms are putting AI to work first in areas where employee strain, patient demand and operational complexity intersect.

The research examined AI use in financial services and insurance, healthcare and medical, and media and advertising, and found that while every sector is moving toward AI, healthcare’s pathway is distinct, focused more on targeted relief than sweeping automation.

“Yet healthcare’s narrower deployment also suggests discipline,” PYMNTS wrote. “The sector is concentrating AI in areas where it can reduce friction now, then build toward broader transformation once data and system integration improve.”