Verified rep counting replaces self-reporting
All industries
Consumer fitness
AI coaching at a fraction of the cost.
Passive workout streams become interactive sessions. Every rep counted, scored and coached on-device.
Personalised quality scoring increases stickiness
Leaderboards backed by real movement verification
Drops into existing apps in days, not months
The challenge
Self-reported reps are a credibility problem.
Consumer fitness apps grew on a simple loop: stream a workout, tap a button when you finish. That loop is showing its age. Users tap when they did not work out. Streaks bend. Leaderboards distort. Premium tiers built on quality engagement stall because there is no signal that distinguishes a real session from a tapped one.
Tap-to-complete fraud
Anyone can claim a workout finished. The behavioural data underneath your product is contaminated.
Coaching that feels generic
Without per-rep quality data, cues are the same for the user who is crushing it and the one who is half-way through their first session ever.
Retention plateaus
Without objective progression, the app feels the same on day 90 as it did on day 1. Users churn just when the unit economics start to work.
How PoseFlow fits
Turn passive streams into objective sessions.
PoseFlow drops on-device pose tracking, rep counting and form scoring into your app. The session becomes a coached interaction. The behavioural data underneath becomes trustworthy.
Reps are verified, not declared.
PoseFlow counts and quality-scores every rep against the trainer-authored movement. Tap-to-complete becomes do-the-movement-to-complete. Streaks earn back their credibility.
Coaching matches the user, not the average.
Per-rep quality scoring picks up depth, tempo, alignment and stability. Cues fire on the specific issue the specific user is having, on the specific rep.
Leaderboards reward actual movement.
Verified-rep leaderboards keep the social loop honest. The user who actually did 50 squats beats the one who tapped through.
Progress is measurable, not vibes.
Session-to-session deltas surface in your existing analytics pipeline. Users see their depth improve. Product sees retention move.
Use cases
Where PoseFlow shows up inside a fitness app.
Three places PoseFlow earns its keep in the first 90 days of an integration.
01
On-demand workout streams
Pre-recorded class plays in the main pane, PoseFlow tracks the user in a corner PIP. Each rep counted and scored against the move the instructor just demonstrated. Form cues surface when the user drifts off pattern.
+18% Average watch-through lift after integration
02
Daily challenges and streak loops
Today's challenge is 60 squats at quality 80+. PoseFlow keeps the count honest. The streak only ticks when the movement actually happened. The behavioural signal underneath becomes a real engagement metric.
63% / 89% Verified completion rate vs self-reported
03
AI coaching upsell
The free tier gets workout streaming. The paid tier gets a coach. The coach reads quality scores the user can't fake and dispatches cues that hit. Premium conversion stops being about content and starts being about value.
2.4× Coach interaction → paid conversion
Integration
How PoseFlow drops into your app.
A typical consumer fitness integration ships in days, not months. PoseFlow is an SDK; it slots beside your existing video player and your existing analytics.
Read the technical docs- 01 Add the PoseFlow SDK to your iOS / Android / web targets.
- 02 Mount `TrackedMovementView` where your video player is, or in a PIP overlay alongside it.
- 03 Load a `.pose` file (we ship a starter library, or your trainers author their own in PoseFlow Studio).
- 04 Subscribe to `onRepCompleted` and `onFormFeedback` to drive your existing UI surfaces.
- 05 Forward the verified rep events into your analytics pipeline. Done.
Common questions
Fitness FAQ
Does it work on older phones?
Yes. PoseFlow runs at 30+ fps on phones five years old. On newer Apple Silicon iPads it hits 60 fps. There is no minimum spec beyond a working camera and a recent iOS or Android release.
How is this different from MediaPipe or a wrapper SDK?
PoseFlow is a full movement-tracking platform. Rep counting, quality scoring, form feedback, an authoring studio. A pose wrapper gives you 33 points on a body; PoseFlow gives you a rep count, a quality score, and a coachable session.
How long does an integration take?
A working integration with rep counting and form scoring against our bundled movements ships in a few days. Authoring your own movement library on top adds a couple of weeks for the first cohort.
Does it need an internet connection?
No. PoseFlow runs entirely on-device. There is no inference call, no per-rep network round-trip, no cloud dependency. Your app stays as offline-friendly as its content layer.
Talk to us
Ready to explore PoseFlow for consumer fitness?
We will prep a technical walkthrough tailored to your stack and your deployment timeline.
Ready to integrate
See how PoseFlow integrates into your product.
Each engagement starts with a technical walkthrough, tailored to your use case.