GEOSPATIAL AI
Every parcel. Every family.
We see what was unseen. Then we score it, plan it, and put the result in the hands of the people doing the work.
WHY THIS IS THE LEVER
Most housing programs fail at the data layer.
They simply don’t know what’s there. Our work starts there — turning a satellite view into a working map of every roofline, every road, every gap. The kind of map a housing ministry can actually plan against.
01 · SEE WHAT’S THERE
A working map of every settlement on Earth.
We pull every public satellite view of a place, then teach our system to recognize the difference between a roof and a road, a vacant lot and a foundation, a permanent structure and a tarp. The result is a precise map — building by building, lot by lot — that didn’t exist the day before.
02 · SCORE EVERY RISK
Flood. Heat. Fire. Wind. One number per home.
Climate isn’t one thing — it’s many overlapping risks, different for every house on every street. We bring all of them together into a single resilience score a ministry can act on: where to retrofit first, where to relocate, where to build differently.
From satellite to map.
Recognize rooflines, roads, retaining walls, infrastructure gaps — at scale, automatically. Hand back a map a planner can actually use.
Ask the map a question.
“Show me every settlement that gained fifty structures in the last eighteen months.” Get back the answer, with sources. In the user’s own language.
Plan before you pour.
Generate site-plan candidates that fit the parcel, the climate, and the community. Hand them to residents to compare and refine, before the first wall goes up.
Open data, by default.
Every dataset we produce ships back to the partner ministry and to the global commons. No extraction. No lock-in.