From Scan to CAD in Hours: The NavVis + Mach9 Workflow for Infrastructure Teams

Historically, surveying workflows have relied on time-intensive, single-point measurements in the field using total stations, paired with CAD software built for manual drafting and modeling. Today's advancements in lidar technology now enable the capture of millions of measurements per second (point clouds), significantly reducing time spent on site. But for many firms, the biggest bottleneck now lies in the office: turning massive point cloud and imagery datasets into reliable, actionable survey deliverables.

Join NavVis and Mach9 for a firsthand look at how two leading surveying and engineering firms, Pennoni Associates and Feldman Geospatial, are overcoming one of the industry's most relevant challenges by leveraging a seamless, end-to-end workflow combining NavVis' wearable lidar with Mach9's AI-powered Digital Surveyor 2.

Key Takeaways

1. Identify infrastructure projects where automation pays off immediately

Not every surveying project justifies workflow automation — but transportation corridors, utility networks, and telecom right-of-way surveys do. This segment shows you how to evaluate project scope and feature density to predict ROI from automated extraction.

• Which project types deliver the biggest time savings with Mach9 — road corridors, rail, utilities
• How to assess feature complexity and scan coverage before committing to automation
• Real project economics: time saved, staff redeployed, and margin improvement

Outcome: You'll know which projects in your pipeline should use automated extraction and how to price them accordingly.

2. Prepare NavVis scan data for automated feature extraction

Mach9's AI requires properly captured and processed NavVis data to extract features accurately. Poor scan coverage or misaligned trajectories create extraction errors that cost more time than they save.

• Capture planning: scan density, overlap, and positioning best practices for infrastructure
• How to process and export NavVis scan data ready for Mach9 ingestion
• Common capture mistakes that break automated extraction and how to avoid them

Outcome: Your field teams will capture NavVis data that feeds cleanly into Mach9 without rework or manual cleanup.