Oura builds its own AI model specifically for women’s health

Oura has built its first custom AI model designed specifically for women's health. The model powers a new version of Oura Advisor that combines medical expertise with personal biometric data to provide health guidance across the full reproductive spectrum.

This marks a shift from simply adding general-purpose AI to existing health platforms. Instead, Oura created a model trained specifically on women's health knowledge, with input from board-certified clinicians and women's health experts.

How does it work?

When users ask women's health questions, the model pulls from a curated medical knowledge base while analyzing personal biometric data. It looks at sleep patterns, activity levels, cycle data, pregnancy information, and stress indicators to provide personalized responses.

The model is designed to be supportive rather than dismissive - a conscious choice that acknowledges how women's health concerns are often minimized in traditional healthcare settings. All conversations stay on Oura's own servers and aren't shared with third parties or used to train other AI systems.

Why does it matter?

"Women's health is too complex - and too often overlooked - to rely on one-size-fits-all systems," said Oura CMO Ricky Bloomfield, MD. "By designing a model specifically for women and grounding it in trusted clinical science and real-world biometric data, we're setting the standard for how responsible intelligence should be built."

As health AI becomes a go-to resource for consumers, specialized models may prove more effective than generic tools that lack physiological context. An Annenberg Public Policy Center survey found nearly 8 in 10 U.S. adults search online for health symptoms.

The context

The timing reflects Oura's user base reality. The company revealed last year that women make up the majority of its users, clearly influencing this investment decision.

The model is currently in testing through Oura Labs, where members can opt in and provide feedback. This approach allows Oura to refine the system with real user input before a broader rollout.