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FitTrack: AI Personal Trainer
Using computer vision to warn users about bad posture in real-time during workouts.
Overview
FitTrack wanted to differentiate themselves in a crowded fitness app market. They had the idea of an 'AI spotter', but didn't know how to implement it technically.
Client Requirements
- Real-time pose estimation on mobile
- Offline functionality
- Voice feedback integration
- Gamified progress tracking
Key Features
TensorFlow.js Integration
PoseNet Models
Privacy-First (On-device processing)
Social Leaderboards
"The AI features are the main reason people subscribe. It really feels like having a personal trainer in your pocket."
Mike T.
Product Manager
How We Built It
We used TensorFlow.js to run PoseNet models directly on the user’s device. This ensured zero latency for coaching feedback and protected user privacy since no video feed was sent to the cloud.
Technologies
TensorFlow.jsReact NativeFirebaseReduxTypeScript
Outcomes
- Viral growth on TikTok due to AI challenge
Visual Transformation
Before
After