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