Uncovr raises $7M to automate surgical documentation

The Next Web reports that Uncovr, a surgical AI startup headquartered in New York and Paris, raised $7M in a seed round led by Index Ventures. The Next Web says other participants included Seedcamp, Frst, No Label Ventures, and Entrepreneurs First, plus angels such as Jean Nehme, Othman Laraki, and Charlie Songhurst. The Next Web reports Uncovr was founded in 2025 by Ines Iraki, Johann Diep, and Professor Eric Vibert and is exiting stealth.

According to The Next Web, Uncovr's software ingests surgical and endoscopic video in real time, drafts the operative report, and suggests procedural and billing codes before the surgeon leaves the operating room. The Next Web quotes CEO Ines Iraki: "Millions of minimally invasive, endoscopic, and robotic procedures are performed through a camera every day, yet the official record is still created afterward, often hours later and outside the flow of care." The Next Web reports that the company says a surgeon reviews and approves every output and that Uncovr says it has analysed thousands of hours of procedures and has a pipeline of more than 400 operating rooms.

Industry-pattern observations: Converting procedural video to structured clinical text and billing codes requires reliable computer vision, robust surgical phase recognition, and clinical NLP tuned to medical nomenclature and coding systems. Companies tackling similar problems typically combine temporal video models, instrument detection, and clinical-NER pipelines to map observations to CPT/ICD codes and operative-report templates. Real-time constraints raise engineering demands around latency, on-premise inference, and integration with hospital EHRs.

Reporting places Uncovr in a growing tranche of startups focused on documentation and workflow automation rather than procedural assist. For practitioners, this trend shifts attention from model accuracy alone to deployment challenges: regulatory compliance, auditability of outputs, human-in-the-loop sign-off, and billing risk management.

For observers: verify independent evidence for the company-stated metrics (hours analysed, 400+ OR pipeline) and look for published validation on coding accuracy, error rates, and integration modes with electronic health records. Watch for regulatory disclosures or peer-reviewed evaluations that quantify clinical and reimbursement impact.