Automated Spatial QA
AI/ML DEVELOPMENT

Automated Spatial QA A Leading Commercial Construction Firm

Automated spatial analysis (Point Cloud vs BIM) reducing manual QA from 5 days to 2 days per construction site.

5 days → 2 days

QA Time

3 Major Structural Risks

Critical Issues Prevented

4 Weeks

Delivery Time

±2cm accuracy

Measurement Precision

Manual, Slow, and Error-Prone

A leader in large-scale commercial construction relied on manual site inspections to track progress. This process was incredibly time-consuming, requiring teams to spend days on-site with measurement tools, leading to project delays and potential human error.

They needed a way to rapidly compare the 'as-built' reality of their construction sites against the 'as-designed' 3D models (BIM). The goal was to implement an Automated BIM Quality Check that could flag deviations automatically so project managers could take immediate action.

Engineers looking at blueprints on a construction site

Building a Data Pipeline

We built a workflow MVP that ingested 3D data from drones and terrestrial scanners, processed it, and delivered actionable insights.

Data Ingestion

Created a secure endpoint to receive large point cloud and photogrammetry data from various on-site scanning devices.

3D Processing

Used a cloud-based pipeline to process raw 3D data, aligning it with the project's master BIM model for comparison.

Deviation Analysis

Developed an algorithm to detect and flag discrepancies between the model and the scan, generating a visual exception report.

Clarity from the Clouds

The workflow MVP completely transformed the QA process. Project managers could now get a detailed progress report within hours of a drone flight, instead of waiting days for a manual survey.

The system caught three critical structural misalignments early, preventing significant project delays and downstream rework. The success of the MVP led to a full-scale rollout across all of the company's projects.

A modern dashboard showing a 3D model of a building