CoreFit on-device pose coach for form feedback.
A Core ML fitness workflow for users who want live exercise guidance without sending camera frames to the cloud.
CoreFit Pose Coach made the workflow easier to explain: the inputs, AI review, human handoff, and business action are all visible in one place.
— Product team
Skeleton overlay on-device
Exercise progress tracked
Feedback shown live
Camera processing stays on device
Fitness feedback needs to be immediate, private, and easy to understand.
A mobile pose coach must show tracking, rep count, and form cues without overwhelming users during exercise.
The workflow needed a visual and operational story that buyers can scan quickly: what comes in, what the AI does, what a human reviews, and where the result lands.
Feedback must update without distracting the user.
Lighting, angle, and occlusion affect landmark quality.
Camera data should stay local for trust.
Users cannot read complex explanations mid-rep.
We designed the mobile surface around live form feedback.
The mobile interface shows pose skeleton overlay, rep count, form score, and local-processing status.
The project is framed around the business workflow itself: the source inputs, AI review, approval points, and final handoff are all visible in one story.
- iPhone frame with pose skeleton overlay.
- Rep counter and form score.
- Specific feedback cues for posture.
- On-device processing badge.
Phone frame
The visual makes the on-device experience explicit.
Skeleton overlay
Pose tracking is visible without using real user imagery.
Score and reps
Progress and quality are shown together.
Local badge
Privacy is part of the interface, not only the copy.
Workflow audit
Mapped source inputs, users, review points, and the final business action.
AI task design
Defined classification, extraction, drafting, prediction, or detection responsibilities.
Human review path
Added approval, exception, and escalation points where judgment matters.
Product narrative
Turned the workflow into a clear buyer story for sales conversations, reviews, and handoff.
- Camera frame
- Exercise mode
- User settings
- Local model
- Landmarks
- Joint angles
- Rep phase
- Confidence
- Form score
- Rep count
- Cue selection
- Safety state
- Overlay
- Voice cue
- Progress
- Workout log
On-device pose coaching needs tight visual feedback with privacy and latency built into the product surface.
Clearer product surface: CoreFit Pose Coach now communicates the workflow through the actual review states, handoffs, and outcomes buyers care about.
Faster buyer clarity: the problem, workflow, proof points, and next action are easy to understand without a technical walkthrough.
CoreFit Pose Coach made the workflow easier to explain: the inputs, AI review, human handoff, and business action are all visible in one place.
- Camera frame
- Exercise mode
- User settings
- Local model
- Landmarks
- Joint angles
- Rep phase
- Confidence
- Form score
- Rep count
- Cue selection
- Safety state
- Overlay
- Voice cue
- Progress
- Workout log
- Human review
- Audit trail
- Quality checks
- Fallback rules
Got a problem AI might solve? Let's find out.
30 minutes. Free. No NDA needed. You leave with a clear yes-or-no on whether to build — and a one-pager you can forward to your team the same day.