Exactly one week ago, the first lines of code for BikeScout were pushed. It didn't start as a commercial product, but as a tool for riders who are tired of being lied to by their GPS apps.
We’ve all been there: your routing app promises a "smooth gravel road," but 5km in, you find yourself waist-deep in sticky clay or carrying your bike over an unrideable rock garden. This is the Geospatial Truth Gap, and BikeScout is here to close it.
The Challenge: Surface Intelligence
Standard maps classify roads by hierarchy (Primary, Secondary, Path). This works for cars, but it’s useless for cyclists. For us, a "path" could be a manicured forest road or a vertical S4-grade descent.
BikeScout solves this by performing Deep Tag Parsing. We extract every metadata detail from OpenStreetMap, surface, smoothness, tracktype, and width.
The Challenge: The Mud Variable
A trail is a living thing. Its condition changes with the sky. Most apps ignore weather history, but BikeScout integrates a 72-Hour Rain Analysis. By cross-referencing rainfall volume with soil permeability (clay vs. sand), our engine predicts the "Mud Risk." If the intelligence says Critical, you better bring a fender or change your route.
The Challenge: Real-World Elevation
GPS data is inherently noisy. Standard GPX tracks are often riddled with micro-oscillations that create "phantom" vertical gains, those jagged profile lines that make a steady climb look like a saw blade. BikeScout doesn't try to "invent" smoothing where it isn't needed; it uses Tactical Decimation to reveal the true effort of the route.
One Week In: The Future
We are just getting started. BikeScout acts as the "brain" that any AI can use to help you plan your missions. In just seven days, we’ve moved from a concept to a functional intelligence tool.