Coaches and computer vision engineers, working from the same side of the net.
SwiftTennis began when coaches kept losing evenings to tagging match video. We asked a simple question: if a camera can already see the ball and the players, why does a human still have to count every point?
The first prototype ran on a single laptop next to a practice court. Today the same idea powers academies, private coaches, and broadcast workflows - still with one camera and no wearables.
Session notes disappear. Different coaches score the same point differently. Players wait days for feedback that should arrive while the match is still fresh.
After every match, someone still has to pause, rewind, and mark points by hand.
Without a shared system, stats depend on who was watching and how tired they were.
Most footage never becomes structured data. Patterns stay invisible.
We treat the video itself as the sensor. Models detect the ball, players, pose, and court geometry from ordinary camera feeds. Scoring logic sits on top of those detections so the output is a full match timeline, not a pile of clips.
First ball and player detectors running on practice footage.
Automatic point and game logic validated against human scorers.
Live use with coaching staff and junior programs.
Dashboard, APIs, and broadcast-oriented deployments.
We measure against real umpires and coaches, not demos alone.
If it needs a new device on every player, it doesn’t ship.
Software assists judgment; it doesn’t replace the person on court.
More sports, deeper stroke models, and tighter integration with the tools coaches already use. Want to see it on your footage?