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Oura’s latest feature puts women’s health at the center


An Oura Ring 4 rests on a wooden surface

Rita El Khoury / Android Authority

TL;DR

  • Oura has introduced its first proprietary AI model focused on women’s health.
  • The feature combines clinician-reviewed research with users’ data to interpret cycle, fertility, pregnancy, and menopause trends.
  • It is rolling out now in Oura Labs within Oura Advisor.

Oura is expanding its focus on women’s health with a new AI model. The feature is the company’s first proprietary AI system and aims to turn ring data into personalized guidance. It is rolling out for testing in Oura Labs within Oura Advisor, the company’s in-app AI assistant. Unlike earlier Advisor updates that used general AI systems, the new tool runs on a custom model built around clinician-reviewed women’s health research.

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Oura Advisor AI Model Womens Health

According to Oura, the system interprets long-term trends, including sleep, cycle tracking, activity, stress, and pregnancy signals, through the lens of broader women’s health knowledge, to provide contextual guidance. The company positions the feature as a conversational tool rather than a medical service, noting that responses are tuned to be supportive and non-dismissive.

Women’s health is a major wearable battleground as companies race to translate data into insights about cycles, fertility, and menopause. A model built around that complexity gives Oura a clearer framework than applying a general chatbot to health metrics. As always, this comes with familiar limitations. AI guidance (even when clinically informed) isn’t diagnostic.

Oura is, however, careful to emphasize privacy as the feature enters testing. The company says the model runs on Oura-controlled infrastructure and that conversations are not sold, shared, or used to train public AI systems. Participation in Oura Labs is optional.

If successful, tools like this could mark a broader shift in wearable health from tracking metrics to interpreting them. The challenge isn’t collecting data anymore as much as turning long-term patterns into guidance that is genuinely useful.

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