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Exclusive: GenHealth AI seeds $13M for payer-facing medical models

Erin Brodwin
Updated Jul 18, 2023
Illustration of a doctor's hands holding a large magnifying glass over a dollar bill.

Illustration: Gabriella Turrisi/Axios

Medical data prediction startup GenHealth.AI collected $13 million in seed funding, CEO Ricky Sahu tells Axios exclusively.

Why it matters: As generative AI applications in health care gain traction, GenHealth differentiates itself by training its models on medical data to help lighten insurers' administrative burden.

Details: Craft Ventures and Obvious Ventures co-led the round.

  • Funds are being used to build out GenHealth's use cases for health insurers and care providers.
  • Sahu declined to say when he expects the company to raise a Series A.

How it works: GenHealth trains what it calls large medical models (LMMs) on medical data to assist payers with tasks like risk adjustment and care management.

  • Its models are trained on anonymized data including patient demographics, disease conditions, procedure and medication codes and costs and published medical research data.
  • Most generative AI health care companies train large language models (LLMs) on speech-based data to assist providers with administrative work.

What's next: Sahu hopes to soon see Boston-based GenHealth apply its models to help streamline efforts like prior authorization and utilization management.

What they're saying: "There's so much more data out there than what comes out of providers' mouths," Sahu says.

  • "In health care, so much medical spending is wasted on services that don't need to happen — that's the space we're in," he adds.

Catch up quick: Sahu and former 1upHealth colleagues Eric Marriott and Ethan Siegel spun GenHealth out of their former employer three months ago.

State of play: Predictive AI medical startups are all the rage of late following the introduction of GPT4 by Open AI, but most train their models on speech-based data. For example:

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