Bridge the gap between captured reality and intelligent models. Workflows that transform scans into BIM-ready geometry and living digital twins of buildings and infrastructure.
From the NXT BLD 2026 stage and the reality capture panel: the local-first cognition stack for 3D spatial AI for AEC. Smart point cloud in, IFC and decisions out, in three days, not six weeks.
3D Spatial AI for AEC: The Offline Stack That Replaces 6 Weeks of BIM Work Read More »
A 10-step Python Guide to Automate 3D Shape Detection, Segmentation, Clustering, and Voxelization for Space Occupancy 3D Modeling of Indoor Point Cloud Datasets. If you have experience with point clouds or data analysis, you know how crucial it is to spot patterns. Recognizing data points with similar patterns, or “objects,” is important to gain more
3D Shape Detection for Indoor Modelling Read More »
