Doximity, OpenEvidence settle healthcare AI lawsuit
Doximity and OpenEvidence reached a settlement in principle on October 15, 2026, ending litigation in the U.S. District Court for the District of Massachusetts concerning alleged efforts to extract proprietary information from a healthcare AI platform Healthcare Dive.
The action was voluntarily dismissed with prejudice on October 16, 2026, covering all claims and counterclaims between the parties Healthcare Executive. The dismissal resolved OpenEvidence's allegations involving corporate espionage, doctor impersonation, and cyberattacks, alongside Doximity's counterclaims involving defamation, false advertising, and unfair business practices.
Settlement Terms Undisclosed
The joint notice filed by both parties did not reveal specific settlement terms, and neither company made a public statement about the resolution Bloomberg Law. No settlement amount, damages award, or penalty was disclosed in court filings or subsequent reporting. Each party agreed to bear its own costs and attorneys' fees as part of the agreement.
The case centered on competitive tensions in the healthcare AI sector, where both companies operate platforms serving clinicians. OpenEvidence had alleged that Doximity attempted to compromise its systems through prompt injection and other technical methods to gain access to proprietary training data and model architectures. Doximity countered with claims that OpenEvidence made false statements about the nature and scope of the alleged incidents.
No Criminal or Regulatory Action
No criminal sentence, civil penalty, or regulatory action was reported in connection with the settlement AI Weekly. The dismissal with prejudice means neither party can refile the same claims, providing finality to the dispute after months of litigation that drew attention to emerging security vulnerabilities in deployed healthcare AI systems.
The settlement reflects broader challenges facing the healthcare AI industry as companies scale agentic systems that access sensitive patient data and clinical workflows. The case highlighted technical attack vectors—particularly prompt injection techniques—that remain a focus of security research and defensive engineering across enterprise AI deployments.