All case studies
Railways
AI-Powered Track Inspection for Indian Railways
Replaced manual track inspections with an edge-AI vision system mounted on inspection coaches, detecting cracks, missing fasteners and ballast deformation in real time across 4,200 km of track.
Client
Zonal Railway Authority
Timeline
14 months
Location
Northern & Western zones, India
4,200 km / week
Inspection coverage
97.4%
Defect detection accuracy
82%
Manual hours reduced
−61%
Avg. response time
The challenge
Manual inspections covered less than 30% of the network monthly, with delayed reporting causing avoidable derailment risks and high maintenance overheads.
Our approach
- Deployed multi-camera edge units with on-device inference at 90 fps
- Trained a domain-specific CV model on 2.1M annotated track images
- Built a centralised maintenance dashboard with severity-tiered alerts
- Integrated with existing CRIS asset management workflows
The solution
An end-to-end perception stack combining edge inference, geo-tagged defect logging and a maintenance intelligence layer that prioritises crew dispatch by risk score.
"RnDVerse compressed what was a multi-year modernisation roadmap into a working system in under 18 months."
