Heidi Health raises $340M to scale AI agents across health systems

Heidi Health raised $340 million to scale its AI Care Partner platform across health systems, signaling growing enterprise appetite for AI agents that augment clinicians rather than replace them. For builders, the funding and product details offer a case study in how to design AI for regulated, high-stakes environments.

The funding and its structure

The $340 million comes from a $100 million Series C led by Blackbird, with participation from Phoenix Court, Point72 Private Investments, and Headline, plus $240 million in growth investment from General Catalyst. The round brings Heidi's total funding to over $430 million, according to Techmeme. The company plans to use the capital to deepen adoption within global health systems and continue building regulatory and clinical safety foundations.

What the AI Care Partner includes

Heidi's platform centers on two core AI agents. Scribe listens ambiently during patient visits to record history and symptoms, update records, provide multilingual support, and prepare for likely questions such as coding suggestions. Evidence delivers in-line-cited, risk-scored summaries drawn from active patient details, uploaded lab results, and live conversation transcripts. The company says Evidence has answered more than 10 million queries since its March launch.

Heidi also shipped its first secure wearable hardware device, Remote, designed for clinical settings from surgery to community clinics, and Dictate, a voice-to-text feature. This hardware-software approach is notable for an AI startup targeting health systems.

Adoption across health systems

Heidi reports an enterprise activation rate of about 62% across major U.S. public and private health systems. In the U.S., Beth Israel Lahey Health in Massachusetts uses the platform. In the United Kingdom, NHS England Midlands selected Heidi as the sole supplier for what the company describes as the largest clinical AI procurement in NHS history.

What this means for AI builders

Heidi's trajectory demonstrates that health systems are willing to adopt AI agents that reduce administrative burden while keeping clinicians in the loop. The design principle of augmentation rather than replacement is critical for trust and adoption in regulated environments. The Evidence component shows how to integrate real-time patient data with cited research, a pattern that could apply to other domains requiring verified outputs. The inclusion of a wearable device also suggests that hardware integration may be a differentiator for enterprise health AI.

Caveats and open questions

The available sources are primarily company announcements and press coverage; independent validation of performance, safety, and clinical outcomes is limited. Pricing details, deployment timelines, and specific regulatory certifications are not disclosed in the provided materials. The 62% activation rate is self-reported and may not reflect long-term retention or clinical impact. Builders evaluating similar opportunities should seek independent evidence of workflow improvements and patient safety outcomes.