How AI is automating Scan to BIM

Why modeling was always the bottleneck

Scanning a building takes hours to days. Turning the scan into a model has traditionally taken weeks, because a person traces every wall, pipe and piece of equipment against the cloud in Revit (see how to convert a point cloud to Revit). Automation aims at that step.

The automated pipeline

1. Pre-processing. The registered cloud is cleaned, subsampled and split into manageable regions, and floors and rooms are found.
2. Semantic segmentation. A neural network labels every point: wall, floor, ceiling, door, window, column, duct, pipe, cable tray, equipment, furniture. Architectures such as Point Transformer V3, and open codebases such as Pointcept, are the research foundation.
3. Instance separation. Points with the same label are split into individual objects: this pump, that pump, each run of duct.
4. Element fitting. Each object becomes a BIM element. Planar elements are fitted as walls and slabs with thickness and height; pipes and ducts as runs with a diameter or section; equipment is matched to a family or modeled as measured geometry.
5. Relationships. Elements are hosted on levels, openings cut into walls, and runs connected, so the model behaves like a model rather than a pile of shapes.
6. Review and QA. Results are checked against the cloud (see how to check a Scan to BIM model) and corrected where needed.

Approaches on the market

For example, EdgeWise has long automated extraction of walls, pipes and structure for modeling in Revit, and the ODA Scan-to-BIM SDK gives developers tools to go from point cloud to IFC. Our Scan to BIM software and services compared page covers the main options in more detail.

Where automation is strong

• Planar architecture. Walls, floors, ceilings and slabs are found reliably.
• Repetitive MEP. Straight pipe and duct runs and cable trays.
• Volume. Thousands of objects that a person would never have time to separate, like every shelf, cabinet and fixture.
• Consistency. The same rules everywhere, with no fatigue at the end of a long job.

Where people are still needed

• What the scanner did not see. No algorithm measures inside a wall. Hidden geometry is inferred and must be flagged.
• Ambiguity. Is it a duct or a boxed-in beam? Context, photos and judgement settle it.
• Design intent. Choosing the right family, type and parameters for your template.
• Sign-off. Someone has to accept the model against the specification.

How to evaluate an AI Scan to BIM provider

1. Send your own scan. Demos on vendor data prove little. Ask for a pilot on a representative part of your site.
2. Open the native model. Check that walls are walls (not generic models), openings cut, levels set and elements editable.
3. Ask for a deviation report against the agreed LOA (see how to write a Scan to BIM specification).
4. Count the objects. Is equipment separated into individual elements, or merged into a mesh?
5. Check formats. Revit and IFC as a minimum; USD if you need a digital twin.
6. Check data handling. Where is the scan processed and stored, and can it stay on site?

How Moving Atoms does it

You upload a scan from any scanner (up to 200 GB per file) and pick LOD 200 to 500. Our pipeline segments the scan and separates every object, and you follow the job from review to delivery in your dashboard. Within 48 hours you get Revit, IFC, STEP, USD and GLB. On-site processing is available when scans cannot leave your network. Open our LiDAR samples to inspect real deliveries, several with Revit downloads.

Frequently asked questions