MyMother is an AI‑powered platform that integrates biometric data from wearables with self‑reported menstrual cycle information to create personalized hormone‑phase models for female athletes. It delivers daily, data‑driven recommendations on training intensity, nutrition timing, focus periods, and recovery, presented through a secure mobile dashboard.
Funding
Funding not disclosed
Founders
Product
Problem
Female athletes often train and recover without accounting for the predictable hormonal fluctuations of their menstrual cycles, leading to suboptimal performance, increased injury risk, and inconsistent training outcomes. Existing fitness trackers and period apps treat menstrual data as a standalone metric rather than integrating it with physiological signals such as heart‑rate variability, sleep quality, and activity load.
Solution
MyMother delivers a wearable‑integrated, AI‑powered platform that continuously ingests biometric streams from devices like Oura rings and Apple Watches alongside self‑reported cycle data. A personalized machine‑learning model learns each user’s hormone‑phase signatures and correlates them with energy, focus, and recovery metrics. The system then generates daily, data‑driven guidance on training intensity, nutrition timing, focus windows, and recovery protocols, turning hormonal variability into a performance advantage. All insights are presented through a mobile dashboard that updates in real time and respects user privacy through end‑to‑end encryption. The beta version is offered free to accelerate adoption and feedback while the core analytics engine remains platform‑agnostic.
Target Audience
The primary users are competitive female athletes and their performance coaches who require granular, hormone‑aware training optimization; secondary users include sports scientists and fitness professionals supporting women’s elite and recreational sport programs.
Features
- Bi‑directional sync with major wearables (Oura, Apple Watch, etc.) to capture HRV, sleep stages, activity, and real‑time heart rate data.
- Cycle‑aware AI engine that builds a unique predictive model for each athlete, mapping hormonal phases to performance variables.
- Daily actionable recommendations covering training load modulation, macronutrient timing, cognitive focus periods, and recovery strategies.
- Contextual alerts that flag high‑risk windows for overtraining or injury based on combined biometric and hormonal signals.
- Secure, HIPAA‑compliant data pipeline with end‑to‑end encryption and user‑controlled data sharing settings.
- Cross‑platform mobile UI delivering concise, coach‑ready summaries and exportable CSV reports for performance analysis.
- Free beta access with continuous feature roll‑outs driven by user feedback and longitudinal data validation.