Warehouses & Logistics
Your WMS is blind. Your cameras aren't — yet.
Built for WMS Integration Lead teams who need real-time visual intelligence without rebuilding an entire vision stack. EdgeReadyAI Hybrid SDK — edge inference where latency, privacy, or connectivity demand it.
Warehouses & Logistics
Count inventory while you move — not during shutdowns
Manual cycle counts hit only 85–90% accuracy, creating stockouts and phantom inventory that disrupt fulfillment. Aisle Wi-Fi gaps break cloud-dependent vision during routine forklift movement. Vision on mobile edge device detects pallets and slot occupancy during routine movement — no aisle Wi-Fi required.
Manual cycle count accuracy: 85-90% accuracy · Inventory accuracy: 99.1% vs 88% baseline
Deployment: edge · Integration: WMS / RFID
More use cases
How EdgeReadyAI fits warehouses & logistics
Operational scenarios where edge and hybrid computer vision deliver measurable outcomes.
Parcel ID When Barcodes Fail
Keep the conveyor running when barcodes don't. Damaged, obscured, or shrink-wrapped barcodes force manual sort interventions — conveyor stops and labor spikes across shifts. Improve parcel identification rate from 87% to 99.2% with edge mode inference.
Real-time Dock Door Utilization
Stop paying thousands per idle truck hour. Idle trucks at docks cost thousands per hour; manual dock scheduling is guesswork without real-time arrival detection. Improve dock utilization from 62% to 89% with hybrid inference.
Warehouses & Logistics
Improve cycle count accuracy — pilot on one aisle
Talk to us about deploying the Hybrid SDK for forklift-mounted inventory awareness in your environment.