TrainSight

TrainSight explores what happens when you stop asking athletes to pause their workout to log data, and instead bring the analysis to them. Using Meta smart glasses worn during a training session, the system captures first-person footage of a user's workout and processes it through an AI model that evaluates exercise form, movement quality, rep and set counts, intensity, and overall session effectiveness. When the workout is done, the user receives a full structured report covering what they did, how well they did it, and what to do next — including recovery recommendations and guidance for future sessions. The goal is a training companion that meets users where they are: in the gym, in the moment, fully present, with no screen in sight.

Too many fitness apps pull people out of their workouts. TrainSight is built around the opposite idea — that the best training tool is one you forget you're using. By pairing smart glasses with AI-driven movement analysis, TrainSight gives users the kind of structured, personalized feedback that used to require a personal trainer, without requiring them to stop, tap, or log anything. The vision is a future where advanced fitness insight is accessible to anyone willing to put in the work, not just those who can afford one-on-one coaching or are willing to spend half their session staring at a phone.

TrainSight is built on a straightforward belief: AI should inform your decisions, not make them for you. The system observes, analyzes, and reports — but what you do with that information is entirely up to you. This matters in fitness especially, where context, feel, and personal judgment are irreplaceable. Beyond the gym, the project also reflects a broader position on how technology should integrate into daily life. By keeping the user in control, prioritizing data privacy, and being transparent about what the system can and cannot assess, TrainSight is designed to enhance human capability without quietly eroding the autonomy that makes improvement meaningful.