Oura, the smart ring maker valued at $5.2 billion, just launched its first proprietary AI model designed exclusively for women's reproductive health. The model handles questions spanning the full spectrum from early menstrual cycles through menopause, marking a significant shift in how wearable tech companies approach gender-specific health insights. It's a direct challenge to competitors like Apple and Fitbit, who've relied on generic AI assistants for health queries.
Oura is making a calculated bet that women's health needs specialized AI, not just another chatbot. The Finnish wearables company announced today it's rolling out a proprietary AI model built specifically to answer questions about reproductive health, from tracking irregular periods to navigating perimenopause symptoms.
The timing isn't coincidental. Women's health tech has exploded into a $50 billion market, yet most wearable companies still treat it as an afterthought, bolting basic cycle tracking onto devices designed primarily for male physiology. Oura is flipping that script entirely.
What makes this launch particularly interesting is what Oura isn't doing. Instead of licensing OpenAI's GPT models or Google's Gemini like most health tech companies, Oura built its own model from scratch. That decision gives them complete control over training data, privacy protocols, and the ability to fine-tune responses based on the millions of data points flowing from Oura rings every day.
The model draws on Oura's treasure trove of biometric data - heart rate variability, body temperature fluctuations, sleep patterns, and activity levels - collected from over 2.5 million active users. That's a dataset most AI labs would kill for, especially given how notoriously underrepresented women's health data is in medical research.
Oura's approach tackles questions that generic AI models fumble. Ask ChatGPT about fertility windows and you'll get textbook answers. Ask Oura's model and it can reference your personal temperature trends, sleep disruptions, and HRV patterns from the past three months. The difference between generic advice and personalized insight.
