Transform Your App with Real-Time Pose Estimation
Human pose estimation for React Native (Expo), iOS, Android and the web. Free on-device MoveNet keypoints — 17 body points, no API key — with an optional exercise engine for rep counting, joint angles and form scores. Runs on TensorFlow.
Built by developers, for developers.
How to implement pose estimation in your applications ?
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
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
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
From the blog
Guides on pose estimation for React Native, the web and mobile fitness.
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 →Introducing the PoseTracker SDK — React Native & webOne engine, three ways to integrate: native React Native, browser JavaScript, or the classic WebView/iframe API.
Read more →React Native pose estimation on iOS & Android (Expo Go)Install offline or light, handle camera permissions, read free on-device keypoints, then unlock exercises with an optional API key.
Read more →Available Pose Estimation Built-in Tools

Measure and track flexibility progress with automated angle detection.
Learn more about the Flexibility Analysis Tool
Compare user poses against reference positions with real-time feedback.
Learn more about the Pose Comparison SystemSimple, Transparent Pricing
Freemium
Perfect for testing and experimentation
€0 Forever free
- Limited pose estimation data
- Fitness repetition counter
- Only non-commercial use
- Up to 200 API calls monthly
Developer
For professional developers and small applications
€50 per month
- Up to 1000 API calls monthly
- Access pose estimation data
- Angle calculations & tracking
- Motion analysis & feedbacks
- Commercial use
Business Plan
Tailored solutions for large projects
From €150 per month
- 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 🚀
Book a demoFrequently 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.