Flo Health

Headlines · 2

1. 4d
   Google invests in Flo Health to bring period tracking to wearables

   Google announced a multi-year partnership with and an investment in Flo Health, the menstrual-cycle tracking app that says it has more than 80 million monthly users; the investment amount was not disclosed. Starting in early 2027, Flo's cycle insights will connect to Google's health platform and combine with wearable measurements including sleep stages, resting heart rate, heart rate variability, skin temperature and respiratory rate, while the companies also plan women-specific products and research into perimenopause, pregnancy and postpartum recovery. Google says data sharing requires explicit permission given separately for each data type and purpose and can be withdrawn at any time, that Flo data will never be used for advertising or sold, and that Google Health Coach algorithms are designed not to log or store sensitive women's health events. The announcement comes after a consolidated class action over period-tracking data allegedly shared with Google and Meta between 2016 and 2019, in which Google and Flo settled for a combined $56 million while Meta did not settle and was found liable under California privacy law.

   TechRadar · 🔥 0
2. 5d
   Flo Health fine-tunes open models with Databricks to boost medical safety and usefulness

   A Databricks blog post describes how Flo Health, a women's health app with 81 million monthly active users, built safer and more useful custom open models on Databricks AI Runtime. Flo first created an evaluation system of 26 AI judges (12 medical-safety, 6 micro-behavior, 8 usefulness) to turn medical standards into a training signal, generated more than 15,000 privacy-first synthetic questions, then ran supervised fine-tuning and DPO on 32 NVIDIA H100 GPUs using LLM Foundry and Compose-RL with MLflow tracking. Flo reports medical safety rising from 34% to about 61%, usefulness from 42% to 76%, and the share of responses meeting both from 16% to 47%, and estimates tailored models can cut inference costs by an order of magnitude versus frontier APIs; it plans to apply the pipeline to newer open-weight models such as Gemma, Qwen and Kimi.

   Databricks Blog · 🔥 0

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