Among the most interesting AI stories this week was an item about a Boston-area startup called OpenEvidence that uses generativeAI to provide answers to clinical questions based data from leading medical journals. The free-to-use app has proved enormously popular among doctors, with some surveys suggesting at least 40% of all U.S. physicians are using OpenEvidence to stay on top of the latest medical research and to ensure they are offering the most up-to-date treatments to patients. On the back of that kind of viral growth, OpenEvidence was able to raise $210 million in a venture capital deal in July that valued the company at $3.5 billion. OpenEvidence is also the same company that a few weeks back said that its AI system was able to score 100% on the U.S. medical licensing exam. (See the “Eye on AI Numbers” section of the August 21st edition of this newsletter.) All of which may explain why, just a month later, the company is reportedly in talks for another venture deal that would almost double that valuation to $6 billion. (That’s according to a story in tech publication The Information which cited three unnamed people it said had knowledge of the discussions.)
A lot of the use of OpenEvidence today would qualify as “shadow AI”—doctors are using it and finding value, but they aren’t necessarily admitting to their patients or employers that they are using it. They are also often using it outside enterprise-grade systems that are designed to provide higher-levels of security, data privacy, and compliance, and to integrate seamlessly with other business systems.
Ultimately, that could be a problem, according to Andreas Cleve, the cofounder and CEO of Corti, a Danish medical AI company that is increasingly finding traction by offering healthcare institutions “AI infrastructure” designed specifically for medical use cases. (Full disclosure: Corti’s partners include Wolters Kluwer, a huge software company that markets a clinical evidence engine called UpToDate that competes with OpenEvidence.)
