The world is being scanned at an unprecedented rate. LiDAR and high-resolution photogrammetry have made it easy to generate massive Point Clouds. But for an appraiser, an engineer, or an insurance adjuster, a point cloud is "dumb data." It tells you where a surface is, but it doesn't tell you what it is.

For this reason, the problem in spatial technology isn't data collection, it's the interpretation of it.

The problem with raw geometry

A raw point cloud is a hollow shell. To a computer, a 10-million-point scan of a load-bearing wall and a 10-million-point scan of a temporary partition look identical. They are both just clusters of (x, y, z) coordinates.

To make this data useful for renovations or insurance, a human typically has to spend hours manually "tagging" or tracing these points in CAD software. This manual step is the friction point that prevents spatial data from scaling.

Bridging the gap with semantic understanding

We are building a tech stack that automates this reasoning layer. Our approach moves through three distinct phases:

  1. Geometric Extraction: Using Computer Vision , we process point clouds to identify primitive geometries.
  2. Object Recognition: Machine Learning models, trained on architectural and structural datasets, categorize these geometries. This is where a "plane" becomes a "wall" or a "floor."
  3. Semantic Reasoning: By integrating LLMs (Large Language Models) capable of multimodal spatial reasoning, we go beyond simple labeling. Our engine can infer the relationship between objects—identifying a "load-bearing structure" versus "non-structural finishes" or recognizing specific material properties and damage patterns.

From capture to intelligence

The future of spatial technology isn't about higher point density, it's about higher reasoning. By automating the transition from a physical scan to a structured, digital understanding of a space, we are removing the human bottleneck.

Our mission isn't just to help machines see buildings, but to unlock the possibilities of what comes next. As we bridge the gap between physical spaces and digital intelligence, we are redefining how humanity interacts with the world around us.