Rallyvision provides an AI‑driven video analysis platform for squash that automatically detects rallies, extracts detailed metrics on shot selection, placement, errors, and movement, and delivers actionable insights via a mobile app.
Funding
Funding not disclosed
Founders
Product
Problem
Squash players and coaches often lack objective, detailed feedback after matches, relying on memory or informal observations, which leads to repeated mistakes and slow skill development.
Solution
Rally Vision offers an AI‑powered video analysis platform that automatically captures squash rallies and extracts comprehensive performance statistics. The system processes match footage to identify decision‑making patterns, shot selection, and movement efficiency, then presents actionable insights through an intuitive mobile app. Coaches can use the data to design targeted training drills, while players receive real‑time feedback to track progress and refine tactics. The platform supports users at all levels—from junior athletes to professionals—and can be adopted by clubs to monitor and develop talent systematically.
Target Audience
Primary customers are squash players, coaches, and clubs seeking data‑driven performance insights to enhance training and competitive results.
Features
- Automated rally detection and segmentation from recorded match video
- AI-generated metrics on shot types, placement, error frequency, and rally outcomes
- Visual heatmaps and timeline visualizations highlighting decision points and movement patterns
- Personalized feedback recommendations for skill improvement and tactical adjustments
- Mobile app interface for on‑court review and easy sharing of analysis with coaches and teammates
- Cloud‑based storage enabling longitudinal performance tracking across multiple sessions