DREAM

Companies that manage fleets of cars, vans, trucks, and heavy equipment need to track the condition of each asset as it moves in and out of a site, but manual inspection relies on people noticing dents, scrapes, or other changes. Human review can miss damage, and without a consistent visual record there is no clear evidence of when or where a change occurred. This creates disputes and uncertainty about who is responsible for new damage and leaves no single source of truth for an asset's condition history.

DREAM captures every vehicle or piece of equipment passing through a gate, lane, or service drive, automatically identifying the asset and building a 3D reconstruction of it from synchronized images. It uses AI to detect new damage by comparing before-and-after visual records, flagging changes like dents or scrapes as soon as they're found. Every pass is organized into a permanent condition record that can be reviewed by date, letting teams move through an asset's history and open evidence from any arrival or departure. The system is designed to deploy across multiple locations and asset types, including passenger cars, cargo vans, semi-trucks, and heavy equipment, without stopping normal operations.