Abridge Receives Additional $150M Investment

Abridge, a Pittsburgh, PA-based company which specializes in generative AI for clinical documentation, received an additional $150M investment.

The Series C investment was led by Lightspeed Venture Partners, who will also join the board. Other new and existing investors included co-lead Redpoint Ventures, with participation from IVP, Spark Capital, Union Square Ventures, Bessemer Venture Partners, Wittington Ventures, Mass General Brigham Artificial Intelligence and Digital Innovation Fund (AIDIF), Kaiser Permanente Ventures, and CVS Health Ventures.

This raise came just 4 months after the $30M Series B.

The company intends to use the funds to expand the team and develop foundation models that draw upon vast troves of multimodal healthcare data.

Led by Dr. Shiv Rao, CEO and Founder, Abridge provides a platform that was purpose-built for medical conversations, improving clinical documentation efficiencies while enabling clinicians to focus on their patients. Its enterprise-grade technology transforms patient-clinician conversations into structured clinical notes in real-time with deep EMR integrations. Their speech and language technologies have been evaluated in 14 languages and functionally support many more. Moreover, its “Linked Evidence” feature, a technology that maps any highlighted region within a summary to the substantiating evidence in the source transcript (and thus to the underlying audio) has become a required capability. The company is actively developing novel ways to personalize notes, integrate more deeply into the EMR, and provide clinicians with after-visit insights.

Today, Abridge also announced a new enterprise agreement with the Yale New Haven Health System, the largest and most comprehensive healthcare system in Connecticut, that will give thousands of clinicians access to Abridge for clinical documentation. Yale New Haven Health has selected Abridge as their generative AI partner in this area of ambient listening. The initial deployment will be focused on reducing the cognitive burden of clinical documentation, enabling clinicians to spend more face-to-face time engaging with patients instead of computers.