Add AI Coach

Carv already collects a rich set of structured metrics from every session (Carv score, balance, edge angles, pressure timing, symmetry, turn shape, G-forces, etc.). An AI layer could use this data to automatically generate a short post-session coaching report that explains what actually happened in the session.

Instead of just seeing numbers and graphs, users could get a short coach-style summary such as:

“Today’s session showed improvement in edge angles and turn consistency compared with your last session. Your Carv score increased from 139 to 144, driven mainly by stronger edge engagement. However, balance remains the biggest limiter — pressure moved to the inside ski early in several turns. Focusing on outside ski pressure earlier in the turn could unlock further gains.”

The report could highlight:

what improved compared to previous sessions

which metrics most influenced the score

where technique broke down

2–3 clear focus points for the next session

This would turn the analytics into actionable coaching, helping users understand what the numbers actually mean and what to work on next. It would make the data feel much more like having a coach reviewing every session rather than just presenting raw metrics.