OpenEvidence, a Miami-based startup founded by Daniel Nadler in 2022, has reached a $15 billion valuation. The company secured $250 million in its latest funding round in September, contributing to nearly $1 billion in total investment over the past 18 months from backers including Andreessen Horowitz, Blackstone, Thrive Capital, and Sequoia.
The AI-powered search engine is reportedly used by nearly two-thirds of US doctors to aid in patient diagnosis and treatment decisions. The platform processed more than 42 million prompts last month, allowing physicians to search medical journals and clinical guidelines. This adoption has occurred largely through word-of-mouth within the medical community.
OpenEvidence operates on an ad-powered model. The company booked $100 million in ad commitments for 2025 by the end of 2023. Projections indicate the startup is on track to generate between $400 million and $500 million through ads by the end of 2026.
OpenEvidence has gained significant traction in a medical software market that has been slow to adopt generative AI. Its entry predates similar AI offerings from established players, such as Wolters Kluwer's AI version of UpToDate, which was released in October 2025. The company now faces competition from large AI firms like OpenAI and Anthropic, which are also entering the healthcare space.
While medical professionals have praised OpenEvidence for easing workloads, its growing influence has drawn scrutiny from researchers. Concerns have been raised regarding the accuracy of the AI's results as doctors become more reliant on the tool for treatment guidance.
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OpenEvidence, an AI-powered search engine for medical professionals, has achieved a $15 billion valuation after securing nearly $1 billion in investment. The platform is used by nearly two-thirds of US doctors to assist with patient diagnoses and treatments, processing over 42 million prompts last month. Its rapid adoption highlights the growing integration of AI in healthcare, while also raising questions about accuracy and dependence on AI tools.