A finished research run on an example topic, shown in full — the findings, the sources behind them and the product versions are all the run's own output, except that a product name may have been changed where it matched an existing brand.
Basic
Holdtrace
A phone-camera app that scans indoor gym walls to auto-detect holds and generate route maps, plus a session tracker for logging climbs.
What to build
MVP
An iOS/Android app using an on-device CNN/YOLO model to detect holds from a photo, overlay a route grid, and let users log attempts against mapped routes.
Why it can be better
Unlike KAYA and TopLogger, which depend on routesetters manually entering data, this auto-detects holds from a photo, closing the gap flagged as no automatic wall scanning.
Revenue model
Freemium app with a monthly subscription (~$6-9) unlocking unlimited wall scans and route history, paid by individual climbers.
Target user
Regular gym climbers who want faster route logging without manual tagging.
Context
The opportunity this answers
Build a phone-camera app that scans any climbing wall to auto-map holds and routes, giving climbers and home-wall builders personalized route and training suggestions.
Why now
Fresh CV datasets and hold-classification models built in the past year finally make automated wall scanning technically feasible, but they remain scattered single-star hobbyist repositories with no packaged product, while chain gyms keep expanding and search demand holds steady at 8,100-18,100 monthly, giving a real, growing user base ready for a tool that turns this raw technology into something usable before a larger incumbent bundles it first.