AI vehicle inspection for gate operations
Focalx is built for the reality of yards: vehicles parked tightly, limited lighting, limited movement between rows, multiple operators, and constant handovers. We help you document condition and securement at the moments when responsibility changes.
Trusted across industries






























Benefits
Built around how gates actually work
Designed for high-throughput gate operations, where speed, accuracy, and traceability are critical.
AI-powered gate inspections
Vehicles are inspected automatically as they pass the gate, capturing condition data without slowing down traffic flow.
Seamless integration with yard workflows
Gate inspections connect directly to yard operations, ensuring consistent data from entry to dispatch.
Instant documentation and traceability
Every gate event is logged with VIN, time, and location, creating a reliable audit trail for claims and reporting.
More Accurate AIAG compliance
The leading damage management platform for Vehicle Logistics
Inspect: AI vehicle & securement inspections
Detect when vehicles get damaged or when they’ve been incorrectly secured.
Stream: automated workflows
Automate tasks after inspections, internally and across collaborating companies, so issues are resolved faster.
Recover: faster claim adjudication
Auto-sync inspection and damage data directly into claims systems and forms for faster, more accurate adjudication.
Don’t pay for damage you didn’t cause
Inspections with damage found in FVL by Focalx AI
increase in damage detection – AI vs. Human
More accurate AIAG compliance
Collaborate
From reception to dispatch – step by step
- Vehicle is delivered and parked in the yard
- Yard operator performs a guided inspection at the parking spot or lane or drives the car though the Focalx Gate
- Focalx AI detects any damage and applies M22 codes
- Securement status is documented where relevant (e.g. straps, wheel chocks)
- Stream creates tasks for repairs, rework, or follow-up with carriers/OEMs
- Every event is tied to VIN, time, user, and location
Custom damage definitions
Different sectors use different standards. Focalx adapts to your coding and applies it consistently at scale.
Severity mapping
Define what counts as damage for your business, or use multi-level scales. Focalx maps AI output to your catefories, mathing how your teams already work.
Industry-standard codebooks
Use established industry codebooks such as AIAG, ECG, AAR or other sector specific standards. Focalx reads and structures damage codes directly from these frameworks, so inspections follow the same definitions used across logistics, insurance and vehicle operations.
Multi-standard support
Operate across multiple standards without changing your workflow. Focalx can map damages to different codebooks at the same time, making it possible to share consistent inspection data between partners, regions and industries that rely on different standards.
Partnership
FocalX - VASCOR partnership
Through our partnership with VASCOR, a market leader in Finished Vehicle Logistics, Focalx brings AI inspections to operations across the US, Canada, Mexico, and India – helping vehicles move faster with fewer damage disputes.
Focalx and VASCOR partners for the North America market
Self-service data analytics software that lets you create visually appealing data visualizations and insightful dashboards in minutes.
Platform
Use cases in finished vehicle logistics
Focalx is built for the entire vehicle logistics chain – but you can start with the parts you control today.
Finished logistics
Focalx gives OEMs and orchestrators one place to see where vehicles were damaged.
Yard operations
Standardized inspections and handover workflows inside your yards and compounds.
Rail operations
Railcar workflows for damage, spacing, securement exceptions, and seal numbers.
Haulway operations
Inspections every time a carrier picks up or delivers a vehicle, tied to VIN and responsibility.
Further reading
Want to see how it works?
Join teams transforming vehicle inspections with seamless, AI-driven efficiency