AI / VRAS Vision™

Detection tuned for infrastructure.

Off-the-shelf vision models are trained on cats and cars. VRAS Vision™ is trained on the defect classes engineers, insurers, and regulators actually pay attention to.

Pipeline

Upload → detect → score → recommend.

A single request runs the same pipeline the platform uses in production: pre-processing, model ensemble, calibration, and downstream recommendation.

01

Ingest

Image, video, LiDAR, or thermal stream.

02

Detect

Model ensemble runs on GPU edge or cloud.

03

Score

Confidence calibrated against ground truth.

04

Recommend

Prescriptive action written into the ticket.

Model Bench

Confidence-scored classes we're production-ready on.

Structural cracks98.4%

Dispatch CAT-3 inspection crew within 72h.

Metal corrosion97.1%

Schedule coating maintenance in next cycle.

Thermal / gas leaks96.8%

Isolate segment; deploy ground robot to confirm.

Roof damage99.0%

Escalate to facilities; open insurance packet.

Solar panel defects97.6%

Flag inverter string for O&M truck visit.

Powerline wear98.2%

Add to next vegetation-and-line management run.

Try

Run a private pilot on your imagery.

Bring a sample dataset. We'll return a scored, verified report within a two-week evaluation window.