Case study · iOS
Tenny
An AI tennis coach that turns a practice video into one clear thing to improve on the next ball.
My role
Sole product designer & engineer — owned strategy, UX, visual design, iOS development, and ML prototyping from concept to launch
Platform
iOS 18+ · SwiftUI · CoreML
Status
In development · App Store launch next
The problem
Practice video contains the answer. Finding it is the hard part.
Players already record themselves, but reviewing a long session means scrubbing through dead time, finding each contact point, comparing technique, and deciding what matters. Most people stop before they reach a useful insight.
I designed Tenny around a tighter promise: point the phone at the court, play, and come back to an organized session where every forehand, backhand, and serve is ready to review.
Success criteria
Define what useful means before designing the interface.
I translated the product promise into three constraints that guided both the experience and the technical architecture.
Remove the review work
Find contact without scrubbing
Narrow each ball contact to roughly 100 ms so a long practice session becomes a sequence of ready-to-review moments.
Make feedback actionable
Prioritize one next move
Give players one clear coaching cue and a relevant drill instead of asking them to interpret a dense metrics dashboard.
Protect practice footage
Keep analysis on-device
Process full sessions locally and use the cloud only when a player explicitly chooses optional coaching.
The flow
Drop in a session. Review every rally. Export what matters.
The experience is organized around the job players already want done: remove the dead time, make every rally easy to inspect, and turn the useful moments into clips worth keeping.
01 · Detect
Find every swing automatically
Wrist-speed pulses and ball-contact audio narrow each hit to roughly 100 ms before a learned temporal model refines the window.
02 · Understand
Track the racket and ball
Custom CoreML models follow racket position, path, and ball movement frame by frame—on the device, without uploading a session.
03 · Coach
Give one useful next step
Instead of a dashboard full of metrics, each swing gets a grade, one specific fix, and a matching drill the player can try immediately.
The outcome
Feedback close enough to use on the next ball.
Tenny connects the original video, a simple grade, and one focused coaching cue in the same place. Players can hear the advice, open a relevant drill, or compare the swing with ideal form.
The goal is not to produce more data. It is to shorten the distance between seeing a problem and trying a better movement.
Product decisions
Complex technology, deliberately quiet interface.
The hard technical work stays behind the experience. A player sees a familiar video timeline, a clear contact marker, a speed-colored racket trail, and coaching written in ordinary language.
Analysis is on-device by default. Cloud coaching is optional and disclosed at the moment it is used. That privacy boundary became a product constraint, not a footnote.
Support
Questions, feedback, or launch interest? Email workingzian@gmail.com.