Geospatial AI assurance protocol
A concept note scoping the first applied domain protocol: adapting Zansn's evaluation harness to geospatial and environmental intelligence workflows.
Whether reliability metrics built for text and tool-using agents transfer to geospatial workflows without modification, or require domain-specific scorers for spatial, temporal, and sensor distribution shift.
- Geospatial shift-test fixture set
- Domain-specific scorer design
- Comparison against general evaluation harness baseline
Run a remote-sensing classification workflow through the general evaluation harness and a geography/sensor-shifted holdout set, then compare degradation patterns.
Geospatial AI assurance requires domain-specific shift tests, covering sensor type, geography, and time, layered on top of the general evaluation harness, because standard benchmark scores do not capture distribution-shift robustness.
The first applied domain wedge
Geospatial and environmental intelligence workflows are Zansn's first applied domain program, chosen because robustness, uncertainty, and data quality are directly testable and map to real-world decisions in remote sensing, agriculture, infrastructure, and disaster response.
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