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FitTrack: AI Personal Trainer

Using computer vision to warn users about bad posture in real-time during workouts.

FitTrack: AI Personal Trainer

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

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

Business Impact

Active Users
50k
1k
Improved
Retention D30
44%
12%
Improved
Bug Reports
Low
High
Improved

Visual Transformation

Before
Before redesign
After
After redesign

Client

FitTrack

Services

Web DesignDevelopmentStrategy