Transform Your App with Real-Time Pose Estimation

Industry-Leading Motion Tracking and Human Pose Estimation Solutions for Mobile Apps. Powered by artificial intelligence and computer vision from TensorFlow.

Built by developers, for developers.

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Average integration

10minutes

10lines / exercise

🌍

90+

Countries

🤸🏽

100K+

Movements analyzed

⏱️

40 ms

Average Response Time

📱

20+

Project in development

How to implement pose estimation in your applications ?

New

Developer SDK

Native pose estimation SDK for React Native (Expo Go) and the web. Free on-device keypoints, optional API-key exercise engine.

✓React Native, iOS, Android & web
✓Free on-device MoveNet keypoints (17 points)
✓Optional API key: reps, angles & form score
✓One integration, every platform

Open the SDK docs →

WebView / iframe API

The classic PoseTracker integration: embed the camera in an existing WebView or iframe with one line of code.

✓Embed via iframe / WebView
✓Multi-platform & low-code friendly
✓Real-time pose & analysis data
✓Best if you already embed a web view

See the API docs →

Built-in Solutions

Ready-to-use motion tracking tools created by the PoseTracker team. Perfect for quick implementation of proven solutions.

✓Multi-platform (iOS, Android, Web, low-code)
✓Deploy in minutes
✓No development needed
✓Production-ready tools

Explore built-in tools ↓

From the blog

Guides on pose estimation for React Native, the web and mobile fitness.

Comparison

Best Pose Estimation Model in 2026: The Real-Time Mobile Guide

MoveNet, MediaPipe, ML Kit, YOLO-pose and Apple Vision compared on real-time FPS for mobile — a data-driven guide to pick the right model.

Read the guide →SDK

Introducing the PoseTracker SDK — React Native & web

One engine, three ways to integrate: native React Native, browser JavaScript, or the classic WebView/iframe API.

Simple, Transparent Pricing

Freemium

Perfect for testing and experimentation

€0 Forever free

Limited pose estimation data
Fitness repetition counter
Only non-commercial use
Up to 500 API calls monthly

Get started

Developer

For professional developers and small applications

€50 per month

Up to 5000 API calls monthly
Access pose estimation data
Angle calculations & tracking
Motion analysis & feedbacks
Commercial use

Get started

Enterprise

Tailored solutions for large projects

Custom pricing

Custom API call limits
All Developer Plan features
Custom exercise and tools development
Integration support
Dedicated success manager

READY TO TRANSFORM YOUR PROJECTS & APPS ?

PoseTracker gives you the tools to provide real-time feedback, enhance client experience, and stand out in a crowded market. Start delivering innovative user experiences with a technology built by developers, for developers 🚀

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Frequently asked questions

Pose estimation for mobile and web apps, answered.

What is the best pose estimation model for real-time fitness on mobile in 2026?

For a single person, in real time, on mobile and across platforms, MoveNet is the common default: in the browser it holds about 34 FPS on a Pixel 5 and 51 on an iPhone 12, where BlazePose sits around 11-12. PoseTracker runs MoveNet on-device on iOS, Android and the web, and adds rep counting, joint angles and a form score on top. See the 2026 model guide →

MediaPipe vs MoveNet vs BlazePose — which should I use?

MoveNet (17 keypoints) is lighter and faster for real-time, cross-platform mobile. MediaPipe / BlazePose (33 landmarks, 3D) is richer but heavier, better when you need 3D or hand and foot detail. PoseTracker is built on MoveNet and handles the camera pipeline and the business layer (reps, angles, form score) for you.

How do I add real-time pose estimation to a React Native or Expo app?

Install the PoseTracker SDK (@pose-tracker/react-native-pose-estimation), wrap your screen in the provider, and read keypoints from the hook. Keypoints are free and run on-device; an optional API key unlocks exercises. It works in Expo Go on iOS and Android. React Native guide →

Can pose estimation run in a web app or the browser?

Yes. The PoseTracker web SDK runs MoveNet in the browser over TensorFlow.js, with free on-device keypoints, from a script tag, an ESM import or a React wrapper. Web guide →

Does it work offline, and on both Android and iOS?

Yes. The offline React Native package bundles the MoveNet model on the device, so inference needs no network; the light package fetches the model at runtime. Both target iOS, Android and the web from a single integration.

Do pose estimation models give rep counting and form feedback out of the box?

No. Every model returns only keypoints and confidence scores. Rep counting, joint angles, a form score and comparison to a reference movement are a business layer you build yourself — or get ready-made from PoseTracker via an optional API key.

PoseTracker

Transform Your App with Real-Time Pose Estimation

How to implement pose estimation in your applications ?

Available Pose Estimation Built-in Tools

Simple, Transparent Pricing

READY TO TRANSFORM YOUR PROJECTS & APPS ?

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