What would an underwriter need before trusting an agent's risk report?
A reference underwriting copilot for geospatial risk, with signed and traceable reports.
Design choice
Every decision the agent makes writes an action credential, a deny-by-default policy bundle sets what it may do and spend, and each report carries checksummed artefacts ready for keyless signing.
In practice
When an agent's analysis will inform a regulated decision, design the audit trail and the policy limits with the workflow, not after it.
What I built
- Natural-language questions decomposed into geospatial analysis steps
- FEMA National Risk Index and BigQuery Earth Engine connectors
- Action credentials for every decision, and OPA/Rego policies that deny by default, cap spend and keep PII at county level
- Reports as PDF, GeoJSON and CSV with checksums and OpenTelemetry traces
Where it stops
A personal R&D reference implementation, not a product. It runs offline on synthetic fixtures by default; Google Earth AI stays stubbed until API access is available, and cloud mode needs your own BigQuery and Earth Engine access. Its evaluation harness (golden questions, ROUGE-L, join integrity) checks the reports' narrative and data joins, not underwriting accuracy.