OpenEvidence markets itself as an AI-powered medical search engine and brain extender for clinicians, delivering citation-linked answers drawn from medical literature to aid decision‑making.

The platform is physician-focused and positioned as a competitor in healthcare AI, aiming at doctors rather than consumers, with ambitions akin to a clinician‑oriented successor to consumer AI health tools.

Its AI models are trained on data from top scientific journals and reinforced by partnerships with major publishers to provide AI-assisted clinical insights.

Revenue is primarily advertising-based, a model the company argues differentiates it from rivals, with annualized revenue reported at over $100 million.

Leading investors in the latest Series D include Thrive Capital and DST, with involvement from GV, Sequoia, Kleiner Perkins, Coatue and others.

Founder notes pressure from larger tech players in AI healthcare but remains committed to keeping OpenEvidence independent, with a potential pathway to public markets following a foundation‑model‑then‑application‑layer sequence.

OpenEvidence has completed its fourth fundraising round in under a year, bringing total funding to nearly $700 million since 2021.

The company asserts a moat built on physician focus, data quality, and hundreds of millions of real‑world consultations, arguing this is hard to replicate.

OpenEvidence surpassed $100 million in annual revenue in January, underscoring rapid commercial traction.

The platform is ad-supported and free for doctors, with broad adoption including significant daily use by a large share of U.S. physicians.

Despite competition from health‑focused offerings by OpenAI and Anthropic, OpenEvidence emphasizes first‑mover advantage and a strong data network as durable differentiators.

OpenEvidence was founded in 2022 by Daniel Nadler and Zachary Ziegler to create a physician‑focused AI chatbot trained on vetted medical data from major journals.