Automated classification, noise filtering, and feature extraction from raw point clouds. Cleaned, labelled, analysis-ready output delivered fast.
→ 02Queryable, semantically-rich 3D models of your site or asset. Built to integrate with BIM, GIS, and inspection workflows.
→ 03Bespoke GIS analysis and cartography for site selection, drainage, vegetation, and infrastructure. Built to answer your specific question.
→Every building, tree, and surface in our digital twins carries semantic labels: material, condition, height, classification. Query the model by question, not by coordinates.
"Show me all façades over 8m in height within 100m of the river." That's the difference between a 3D model and a digital twin.
Custom mapping turns elevation, hydrology, vegetation, and built-up data into answers. Flood risk per catchment. Drainage asset networks. Site suitability at 1m resolution.
Delivered as interactive web maps, static cartography, or raw GIS layers — whichever your stack needs.
Most geospatial work still runs on manual labour. Classifying points, filtering noise, generating 3D models; all done by hand over days or weeks.
We use machine learning where it genuinely helps: automated classification of ground, vegetation, and structures; semantic segmentation that turns point clouds into queryable data; anomaly detection on digital twins.
Everything else stays human, because judgement and quality assurance should. The result: faster delivery, lower cost, outputs that are actually useful downstream.
Share a sample dataset or a brief. Within two working days you get a fixed-fee proposal, timeline, and scope of delivery.