AI Fitness Coach MVP: Computer-Vision Form-Check and Personalized Plans Live in 3 Weeks
SpeedMVPs built a React Native app backed by a FastAPI inference service running MediaPipe Pose on the server side, streaming landmark scores over WebSockets for sub-200 ms rep feedback. GPT-4o generated adaptive weekly workout and macro plans from onboarding biometrics, goal tags, and logged session data stored in PostgreSQL with pgvector for workout-similarity retrieval. The entire stack — inference, LLM orchestration, auth, and push notifications — was deployed to Vercel edge functions and a GPU-backed modal.com endpoint within the three-week window.
Project Overview
What We Built
- SpeedMVPs built a React Native app backed by a FastAPI inference service running MediaPipe Pose on the server side, streaming landmark scores over WebSockets for sub-200 ms rep feedback. GPT-4o generated adaptive weekly workout and macro plans from onboarding biometrics, goal tags, and logged session data stored in PostgreSQL with pgvector for workout-similarity retrieval. The entire stack — inference, LLM orchestration, auth, and push notifications — was deployed to Vercel edge functions and a GPU-backed modal.com endpoint within the three-week window.
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