On Feb. 24, 2026, Oura announced the debut of its first proprietary AI model designed to power Oura Advisor and deliver personalized guidance across the full reproductive health spectrum. The model, available opt‑in through Oura Labs in the Oura app, covers questions from early menstrual cycles through menopause and incorporates long‑term biometric trends. Oura says the model is grounded in established medical standards and reviewed by its in‑house team of board‑certified clinicians and women’s health experts. The company emphasizes the tool is advisory only—not a diagnostic service—and that conversations remain on Oura‑controlled infrastructure.
Key takeaways
- Launch date: Oura publicly announced the model on Feb. 24, 2026, and has rolled it out inside Oura Labs, the app’s opt‑in experimental hub.
- Scope: The model supports queries spanning early menstrual cycles through pregnancy and menopause, addressing the full reproductive health continuum.
- Data inputs: Oura says the model combines clinical research and medical standards with user biometric signals across sleep, activity, cycle, pregnancy, and stress trends.
- Clinical review: Knowledge sources and guidance were reviewed by Oura’s board‑certified clinicians and women’s health specialists, per the company statement.
- Privacy and hosting: Oura reports the model is hosted entirely on Oura‑controlled infrastructure and that conversations are not sold or shared externally.
- Product positioning: The model powers Oura Advisor (the app’s chatbot) and is described as intentionally non‑dismissive and emotionally supportive, but not a replacement for clinical diagnosis.
- Market signal: Oura previously told TechCrunch its fastest‑growing segment is women in their early 20s, an audience the company says helped shape this development.
Background
Interest in AI assistants for health questions has grown rapidly as consumers seek immediate, personalized insights between clinical visits. Generalist chatbots and large language models have expanded health‑related use cases, but they are often trained on broad datasets that lack domain specificity for reproductive medicine. Wearable companies such as Oura sit on longitudinal biometric signals—sleep patterns, activity, HRV and cycle tracking—that proponents say can add context to symptom questions and trend interpretation.
Historically, women’s health and reproductive care have been under‑served by technology and research prioritization, contributing to demand for tools tailored to menstrual cycles, perimenopause and pregnancy. Oura’s move follows a broader industry trend of product teams developing verticalized models for specific clinical domains, combining clinical review with device data to reduce generic or misleading responses from generalist systems.
Main event
Oura disclosed that the new proprietary model is available inside Oura Labs—an opt‑in area of the app for experimental features—where users can enable Oura Advisor to route women’s health questions to the specialized model. When prompted, the chatbot references its curated research and knowledge sources while analyzing the user’s relevant biometric signals and historical trends to generate tailored insights.
The company said the model was trained and validated against established medical standards and peer‑reviewed literature, and that clinical staff—described as board‑certified clinicians and women’s health experts—review the knowledge base. Oura emphasized the assistant is not intended to provide diagnoses or treatment plans; the company frames the model as an informative, supportive tool that augments user understanding rather than replacing clinicians.
In accompanying communications, Oura noted the system is hosted entirely on its own infrastructure and that conversations are not sold to third parties. Access is gated by explicit user opt‑in via a menu setting in the upper‑left of the Oura app, reinforcing a consent‑based deployment for the experimental feature.
Analysis & implications
Oura’s vertically focused model reflects a strategic attempt to combine device telemetry with curated clinical guidance—a proposition intended to improve personalization relative to generalist models. By anchoring responses to medical standards and internal clinical review, Oura aims to reduce hallucination risk and deliver evidence‑aligned advice, but the approach hinges on ongoing oversight, transparent provenance of knowledge sources and robust update processes.
Privacy and security will be central to user trust. Hosting on Oura‑controlled infrastructure and the pledge not to sell conversations are meaningful safeguards, yet independent audits, differential privacy techniques or third‑party assessments would strengthen those claims. Regulators are increasingly attentive to AI in health; although Oura positions the tool as non‑diagnostic, how regulators assess claims, labeling and consumer communication will shape future deployments.
Clinically, the model can help users interpret patterns—such as cycle‑linked sleep changes or perimenopausal symptoms—by combining biometric trends with clinical context. That said, the model’s effectiveness will depend on validation against clinical outcomes and real‑world performance across diverse populations, including under‑represented groups in reproductive health research.
Commercially, Oura’s emphasis on women in their early 20s points to a product play: differentiated AI features could deepen engagement and retention among a growing user cohort. However, competition from other wearables and health AI startups means execution, clinical credibility and privacy guarantees will determine whether the feature moves the needle on adoption and monetization.
Comparison & data
| Feature | Oura women’s‑health model | Generic health chatbots |
|---|---|---|
| Personalization | High — uses long‑term biometric trends | Limited — relies on user prompts and general data |
| Clinical review | Internal board‑certified clinicians | Varied — often no formal clinical governance |
| Hosting & privacy | Oura‑controlled infrastructure, opt‑in | Depends on provider; may share metadata |
| Scope | Reproductive health (cycles → menopause) | Broad medical and non‑medical topics |
The table highlights qualitative contrasts between a verticalized, device‑integrated model and generalist chatbots. While Oura’s approach promises tighter personalization through telemetry, it also raises expectations for clinical governance, auditability and demonstrable safety. Future public validation—such as peer‑reviewed studies comparing AI guidance to clinician recommendations—would clarify performance and limitations.
Reactions & quotes
Company leadership framed the release as both a product and responsibility milestone, stressing clinical grounding and user safety.
“This custom model is a fundamental shift in how we responsibly deploy AI in health to meet the needs of our members,”
Ricky Bloomfield, MD, Oura Chief Medical Officer (company statement)
Oura additionally pointed to demographic trends shaping product priorities.
“Our fastest‑growing user segment is women in their early 20s, and this influenced where we invested in AI,”
Dorothy Kilroy, Oura Chief Commercial Officer (prior interview with TechCrunch, Oct. 2025)
Unconfirmed
- Independent validation: Oura has not (publicly) released peer‑reviewed trials showing the model’s clinical accuracy versus clinician assessment.
- Dataset representativeness: It is unclear how diverse the training and review datasets are across age, race, and health status.
- Regulatory determinations: No public regulatory filings were cited that define whether future versions might be classified as medical devices.
Bottom line
Oura’s proprietary women’s‑health AI model is a notable example of verticalizing AI for a specific clinical domain and pairing it with wearable telemetry. The company’s emphasis on clinical review, device‑hosted infrastructure and opt‑in access addresses some common concerns about privacy and safety, but independent validation and transparent governance will be crucial for broader trust and clinical uptake.
For users, the feature may provide more tailored, contextualized explanations of cycle‑linked changes and perimenopausal symptoms than generic chatbots. Policymakers, clinicians and consumer advocates should watch how Oura documents clinical performance, handles edge cases, and communicates limitations to avoid overreliance on advisory AI in place of medical care.