GEOSPATIAL AI · MACHINE LEARNING
AI that produces reviewable territorial evidence.
GeoSAT combines remote sensing, spatial data and machine learning to prioritise human review, detect change and automate repetitive analysis. Models are evaluated against labelled evidence and remain part of an auditable operational workflow.
What we deliver
Land-cover classification
Repeatable classification pipelines using satellite imagery and reviewed training data.
Change detection
Deforestation, urban expansion and land-use alerts prioritised for expert validation.
Cadastral quality checks
Automated detection of inconsistencies, outliers and records requiring field or desktop review.
Decision-support models
Spatial indicators and forecasts delivered with assumptions, confidence and monitoring criteria.
Evidence from our track record
- GeoSAT has delivered geospatial analytics for cadastre, environmental monitoring and agriculture.
- Production workflows combine model output with expert validation instead of treating AI as an unquestioned answer.
- The same team can connect models to databases, GIS services and institutional applications.
Technology selected for the operating model
A controlled implementation path
- 01
Inventory
Data, workflows, integrations, constraints and acceptance criteria.
- 02
Pilot
A representative workflow tested with real data before broad commitments.
- 03
Operate
Handover, monitoring, support and measurable service-level responsibilities.
Start with the workflow and evidence—not with a preferred product.
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