How I Built Real-Time AI Form Correction Into a Mobile Fitness App

If you've ever done squats wrong for months and only found out when your knees started hurting — this article is for you. I built a fitness app that watches you exercise through your phone camera and tells you in real time when your form is off. Not after the rep. Not in a post-workout summary. Right now, while you're mid-squat. Here's how the technical stack works — and how you can build something similar. The Core Problem Most fitness apps track reps. Count sets. Log weights. That's useful data, but it doesn't answer the most important question: are you actually doing the exercise correctly? Bad form leads to injuries, slower progress, and wasted time. A personal trainer would catch these issues instantly. A fitness app historically could not — until pose estimation models became fast enough to run on mobile. How Pose Estimation Works Modern pose estimation models (MediaPipe, MoveNet, PoseNet) detect key body landmarks from a video frame and return their 2D/3D coordinates. For a squa