AxePro is a GIS-powered booking platform built for property-service businesses in Nairobi, designed to solve a simple but costly problem: turning “Can you come to my property?” into a confirmed appointment without the usual back-and-forth.

We built the experience around what actually happens in the field. A customer selects a service, enters their property location, and AxePro uses location intelligence to determine the appropriate service area, qualified technician, travel requirements, and appointment slots that can realistically work. Instead of showing generic availability, the system accounts for technician schedules, existing bookings, service capabilities, and road travel between appointments. Customers can then confirm, reschedule, cancel, or manage their booking, while the owner gets an operational dashboard showing bookings, technicians, routes, conflicts, and schedule changes.

The key idea is that location isn't decoration — it drives the booking decision. AxePro connects the customer, their property, the service area, the technician, and the route into one workflow. This reduces the manual coordination that normally happens through calls and WhatsApp messages and gives both the customer and business owner a much clearer path from inquiry to completed service.

We built AxePro to feel like a real product rather than a static prototype: real booking data, spatial service areas, technician capability matching, road-aware scheduling, route management, rescheduling, reassignment logic, and post-booking management are all part of the experience.

AxePro turns “Can you come tomorrow?” into “Your appointment is confirmed.”

I built a database a few months ago to store a few different kinds of spatial datasets. Buildings, roads, land-suitability scores, all for Denver. The pipeline is here: https://lnkd.in/gYWTNFxq

Then I got curious and tried the GeoSQL skill with claude together with Dekart, inspired from Volodymyr Bilonenkor. The idea is that you describe the map you want in plain English, and it writes the spatial SQL, checks it, and renders the result.

Here is some of what I made:

Buildings colored by height, then pulled up into a 3D skyline

Buildings that actually fall inside the flood hazard area, 2,084 of them

A land-suitability choropleth across 268k parcels

Tall buildings sitting near a primary road, layered over the road network and flood zones

What I liked most is that it checks its own work. Row counts, areas, coordinate systems, all validated in SQL before anything gets drawn. So I actually trust the map.

If you do any GIS work, it is worth a look.