Autonomous spatial workflows built on the data infrastructure we already deliver: natural-language spatial queries, monitoring agents, and a governed audit layer.
Watching incoming imagery, telemetry or sensor streams for the conditions that matter is a recruitment problem before it is an engineering one, and agent automation without governance - audit trails, rollback paths, human checkpoints - is a liability on any consequential spatial decision.
Conversational interface to your spatial database. Ask in plain English ('show me all assets within 500m of the M25 with maintenance overdue') and get answers against live data.
Agents that watch incoming imagery, telemetry, or sensor streams and surface conditions exceeding thresholds. Human checkpoint on every consequential action.
Audit logging on every agent action. Schema-validated outputs, rollback paths, human-in-the-loop on consequential operations. Engineered from day one.
| Stack | LangChain / LangGraph, MCP servers, PostGIS function-call schemas |
|---|---|
| Maturity | Tier 1 (NL query, classification, QA) is mature in production. Tier 2 (monitoring agents, autonomous reports) is shipping in pilots. |
Review of the spatial infrastructure you already run, and where a natural-language query or monitoring agent fits, with a human checkpoint.
SoW, milestones and the governance and audit scope, under an English-law contract.
Weekly demos, CI/CD and observability from day one, with schema-validated outputs and rollback paths built in.
Extend from Tier 1 (NL query, classification, QA) toward Tier 2 (monitoring agents, autonomous reports) as it matures. You keep the code and the team.
Vendor-neutral platform evaluation, architecture design and migration planning, technical due diligence and team training, across open-source and proprietary GIS stacks.
We bridge GIS and BIM: point clouds, terrain, BIM and live IoT feeds fused into one queryable browser environment. No plugins.