Belay AI shows a camera-only computer vision stack for climbing gyms: scan a QR code, climb, and get technique feedback on your phone without installing an app. The core idea is to make movement analysis feel like part of the session, not a separate “record and review” workflow, by packaging everything as a web app that opens instantly after the scan. https://belay.ai/
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In the demo, the system tracks a climber’s path on the wall and estimates balance-relevant signals like center of gravity plus extension/compression patterns, essentially turning video into kinematics. Under the hood this implies markerless pose estimation, temporal smoothing, and trajectory features that can survive occlusions, fast moves, and varied lighting, while still staying interpretable for coaches who want “what to change next” rather than raw telemetry.
A second thread is safety: beyond post-climb analysis, they’re aiming for real-time mistake detection in belay workflow (rope management and other high-risk behaviors), where earlier warning matters more than perfect scoring. The conversation was filmed at Web Summit Lisbon 2025, and it’s interesting how the product direction keeps technique coaching and incident prevention on the same perception pipeline, just with different thresholds and response timing.
The business model is gym-first (subscription for the venue, free for climbers), which fits the installation pattern: fixed cameras watching the wall, identity linking via the QR flow, then lightweight visual re-identification cues (like clothing color) to keep sessions separated. That design choice also opens the door to gym-wide analytics: progression over time, comparing attempts, and eventually a “coach voice” layer that can convert detected posture issues into short, actionable cues.
They also sketch a more social/competitive roadmap: auto-generated highlight clips, style scoring, friend challenges, livestream overlays, and even processing archived footage of elite climbers to explain technique differences. The most credible angle is that once you can reliably segment a climb and extract consistent motion features, you can reuse the same engine for ranking, content creation, and competition tooling without changing the capture setup.
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