Scan to BIM
Scan To BIM
Transforming Raw Point Clouds into Intelligent BIM Assets
Renovation and expansion projects often fail due to inaccurate legacy drawings. We bridge the ‘reality gap’ by converting high-definition laser scan data into precise, information rich 3D models. Our Scan-to-BIM workflow captures the exact ‘as-built’ conditions of complex industrial and commercial facilities, providing a millimeter accurate digital foundation that eliminates the risks of onsite clashes and design guesswork.
Core Modeling Deliverables
- Point Cloud Registration
- Structural Skeleton Extraction
- Clash Detection Analysis
- Architectural As-Builts
- MEP Pipe & Duct Modeling
- Family Creation & Revit Assets
The Reconstruction Protocol
From Laser Precision to Parametric Intelligence
Our Scan-to-BIM workflow is a meticulous process of ‘Reverse Engineering’ the physical environment. We begin by processing raw LIDAR data, cleaning noise, and registering multiple scan stations into a unified coordinate system. Our modelers then author parametric geometry directly over the point cloud, ensuring that every pipe, beam, and wall is represented at the required Level of Development (LOD 200 to 400). This results in a ‘Living Model’ that serves both the design phase and long-term facility management.
Statistics
- 2mm Modeling Precision (Ensuring the digital model mirrors the physical reality with extreme fidelity).
- 50% Reduction in Site Visits (Eliminating the need for manual measurements and re-surveys).
- 5,000,000+ Square Feet (Of complex industrial space modeled from laser scans).
- 100% Clash-Free Design (Verified against existing conditions to prevent onsite rerouting).
Scan-to-BIM Insights (FAQ)
We offer flexibility ranging from LOD 200 for basic spatial planning to LOD 400 for fabrication-ready MEP and structural models.
Yes. We process data from all major hardware providers (Leica, Faro, Trimble) in formats like .RCP, .E57, and .PTS.
While we model what is visible in the scan, we use ‘placeholder’ geometry for inferred runs based on logical engineering paths, clearly tagged for field verification.
