Inside our AI-accelerated pipeline: from raw point cloud ingestion to classified LAS delivery at 97.2% accuracy.
Delivering 500 km of classified LiDAR in 4 days requires a pipeline where every stage (ingestion, classification, QA, and export) is designed for throughput from the start, not retrofitted onto a process built for smaller jobs.
Raw point cloud ingestion runs in parallel across the full corridor, tiled to a size that keeps each unit of work independent and restartable. The AI classification stage processes tiles as they land, rather than waiting for the full corridor to finish ingesting.
Every classified tile passes through a validation stage against known control points and a sample-based manual QA check, catching systematic classifier errors before they propagate across the corridor rather than after full delivery.
The result is classified LAS delivery at 97.2% accuracy on a 4-day timeline, a schedule that would not be achievable with a purely manual classification workflow at this scale.
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