OpenEvidence’s Daniel Nadler

Mauricio Candela for Forbes

OpenEvidence, which Forbes profiled in July, has been signing up users fast. Its ultimate goal: To not just help doctors find existing medical research, but to create medical superintelligence.

OpenEvidence’s new funding round, announced Monday, has made the startup behind an AI search tool for doctors much more valuable: worth $6 billion, up from $3.5 billion in July. It’s also made Daniel Nadler, the company’s CEO and cofounder, much richer. Forbes estimates Nadler’s net worth has climbed to $3.6 billion after the fundraise, up more than 50% from the $2.3 billion he was worth three months ago—not that he seems to have noticed.

“I just work 100 hours a week and eat cereal,” Nadler tells Forbes, with a laugh. “The more I get into this, the less that anything other than work matters.”

GV (Google’s venture arm) led the new $200 million investment. Thanks to meteoric growth, the Miami-based company, featured on the 2025 Forbes AI 50 list, has garnered the attention of marquee Silicon Valley backers. Other investors in the latest funding round include Sequoia, Kleiner Perkins, Blackstone, Thrive Capital, Coatue, Bond and Craft.

Forbes profiled the 42-year-old Nadler in July, as the company was gaining traction with its ChatGPT-for-doctors model that can help physicians stay on top of the flood of medical research. The startup’s proprietary algorithms search millions of peer-reviewed publications, including in top journals like the New England Journal of Medicine and the Journal of the American Medical Association, to help doctors find the best answers fast, with full citations to papers so doctors can read more for themselves.

The software is free for verified doctors to use and makes money through advertising, much like Google does. In September, OpenEvidence announced its first acquisition—the purchase of AI advertising outfit Amaro to help analyze and roll out ads faster.

Doctors have been quick to adopt the AI tool, which is already being used by 40% of physicians in the United States. Since July, OpenEvidence’s clinical consultations have increased to 16.5 million per month, from 10 million per month, Nadler claims. “Normally that would take three years,” he says. “I mean, it’s crazy.”

But Nadler sees the biggest potential beyond its existing search capabilities–to help doctors not just find existing research, but to expand medical knowledge. “The next phase for us is to push out the frontiers of human knowledge to reach medical superintelligence,” he says.

He compares OpenEvidence’s strategy with how Google Street View powered maps: “Our doctors become the Google cars with the funny cameras on.” As a doctor sees a patient with a rare disease or a complex clinical history, those observations will become part of the company’s data, allowing it to leverage knowledge from doctors across the country. “You’re not so much crowdsourcing as expert sourcing and experience sourcing medical knowledge,” he says.

“The next phase for us is to push out the frontiers of human knowledge to reach medical superintelligence.”

OpenEvidence cofounder Daniel Nadler

Nadler, a Toronto-born Harvard Ph.D. in political economy, sold his previous company, AI analytics startup Kensho, for $550 million in 2018. He poured some of his winnings into OpenEvidence, which has allowed him to keep a large stake in the company, estimated to be nearly 60%. In July, the startup raised $210 million in a round led by GV.

They’re betting on Nadler’s vision of using AI to address the flood of medical information. It’s an enormous issue, and only getting bigger. Medical literature is proliferating at a meteoric rate–doubling in size every five years–as new treatment options like gene therapies are developed and scientists learn more about how different diseases and drugs may interact with each other. In July, OpenEvidence claimed it had booked $50 million in annualized revenue from its advertising model. Nadler now projects annualized revenue will reach $100 million in 2026.

“There are enormous first-mover advantages,” he says. “Something has to be 100 times better to switch from a free product.”

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