①OpenEvidence is reported to have achieved a 100% accuracy rate in the US medical licensing exam. ②Currently, OpenEvidence has been implemented in more than 10,000 hospitals and clinics across the United States, and more than 40% of physicians use OpenEvidence. ③In Japan, Ali Health’s AI product “Hydrogen Ion” recently completed internal testing and is now available for download with product logic similar to OpenEvidence.
STAR Market Daily News reported on January 22 that AI healthcare company OpenEvidence recently announced the completion of a $250 million Series D funding round led by Thrive Capital and DST Global.
The startup has raised a total of $700 million in funding over the past year, according to OpenEvidence. Investors include Sequoia Capital, Google, NVIDIA, Kleiner Perkins, and Blackstone. Since securing its first outside funding last February, the company’s valuation has now jumped from $1 billion to $12 billion.
According to the data, OpenEvidence’s eponymous product is called “ChatGPT for Physicians” and serves as a professional AI healthcare tool that can provide real-time answers to clinicians, using references primarily drawn from professional medical literature. According to the company’s report, in August 2025, the company’s artificial intelligence model achieved a 100% correct answer rate on the United States Medical Licensing Examination (USMLE).
One day in 2025, a 49-year-old male patient with hypertension came to the Mayo Clinic in Rochester, Minnesota for follow-up. Despite compliance with the drug regimen, the patient’s blood pressure remained persistently above target levels, necessitating discontinuation of treatment. After entering the patient’s symptoms into OpenEvidence, the system immediately recommended adding spironolactone and provided detailed supporting references. The researchers noted that the tool strengthened physicians’ decisions to use spironolactone and demonstrated superior performance in chronic disease management.
Niket Patel, M.D., of Drexel University School of Medicine in Philadelphia, praised OpenEvidence, saying, “OpenEvidence provides real-time integration and access to medical literature, which is especially useful for medical students during clinical rotations.” His team believes that the tool’s user-friendly design and focus on clinical evidence make it a valuable and easy-to-use alternative for diagnosis and treatment.
The company’s founder, Daniel Nadler, claims that more than 40% of U.S. physicians use OpenEvidence. “What we do is help physicians make high-risk clinical decisions at the point of care,” he added. “This product is not trained on the internet or social media, where low-quality medical information may be presented.”
OpenEvidence is currently deployed in more than 10,000 hospitals and clinics across the United States. In December 2025 alone, we supported approximately 18 million clinical consultations from logged in and verified physicians and healthcare professionals in the United States. This figure is a significant increase from around 3 million consultations per month a year ago, confirming the rapid adoption of the platform.
Notably, OpenEvidence was one of the first AI startups to rely on advertising revenue, with annual revenue expected to exceed $100 million by 2025. Nadler said that compared to subscription-based models, advertising models are likely to gain faster acceptance and more widespread adoption among users. Businesses can promote their products through video ads within the OpenEvidence application.
Recently, many AI healthcare tools have appeared. Today, Amazon launched Health AI, an AI-powered healthcare assistant that provides personalized recommendations based on members’ medical records, test results, and current medications. Domestically, Ali Health’s AI product “Hydrogen Ion” recently completed internal testing and is now available for download for clinical and research-focused physician groups with similar product logic to OpenEvidence.
CITIC Securities believes that the logic of AI healthcare will fundamentally change in 2026, with a central shift being clearer and stronger payer ownership for AI healthcare this year. It is predicted that 2026 will be the year when AI healthcare enters the C-end market and is expected to see commercial expansion, potentially leading to a reassessment of the value of the ToC channel. The focus should be on five key areas and their related targets: AI medicines, grassroots AI healthcare applications, medical data distribution and trading, AI pathological diagnosis, AI healthcare models, and C-end expansion channels.
Regarding specific investment targets, Zheshang Securities said that driven by national strategy and market demand, AI healthcare applications have entered the rapid stage of commercial implementation. Recommended focus areas include Meinian Health (AI + Health Management) and Anbiping (AI + Pathology). Hua Fu Securities pointed out that huge opportunities exist in undervalued AI healthcare applications, with visible growth in AI-related revenues and accelerating trends towards commercialization. Notable companies include Kangzhong Medical, Runda Medical, and Jiahemeikang.
