I build the spatial systems that
map reality for institutions.

I grew up in Zimbabwe, studied Geoinformatics at the University of Zimbabwe, and got obsessed with a simple idea: almost every problem — land rights, flood mapping, infrastructure planning, mortgage lending — has a geography to it. If you can see it spatially, you can solve it faster.

That obsession turned into a career architecting the GIS systems that Zimbabwe's government and financial institutions now run on. The eCadastre that replaced a paper national land register. The mortgage platform that lets a commercial bank evaluate properties spatially. The land information system that replaced paper-based ministerial approval chains. I was the systems architect on the teams that delivered them — and they aren't prototypes, they're live, national-scale production systems.

Why Drones

Drones close the gap between satellite imagery and ground truth. In places like Zimbabwe where addresses are informal and land records are paper-based, a drone can capture reality in hours. That fascinates me. I'm actively building drone-to-GIS pipelines — from raw imagery to point clouds to queryable PostGIS layers — and working toward my CAAZ piloting certification.

Why AI

Manual digitization is slow. Pattern recognition in spatial data — identifying illegal mining, detecting crop stress, classifying land use — is where machine learning changes everything. The next leap in GIS isn't about better maps. It's about maps that think — detecting patterns, classifying land use, flagging anomalies without a human reviewing every pixel. I'm building toward that.