NAVA Vision AI: InventoryView – Warehouse Inventory Tracking FREE PoC

The NAVA Vision AI: InventoryView enables organizations across warehousing, retail distribution, manufacturing, industrial operations, automotive, ports, construction, energy, and oil & gas to gain real-time visibility into inventory and asset movement using computer vision.

InventoryView uses your existing CCTV/IP camera network, enhanced with optional data from RFID tags, barcodes, BLE/UWB devices, GPS trackers, telematics systems, and WMS/ERP integrations, to build a unified visual inventory intelligence layer. The system automatically detects and tracks:

• Pallets
• Cases & SKUs
• Raw materials
• Finished goods
• Containers & totes
• Tools & industrial equipment
• Rental equipment & parts
• High-value inventory
• Yard or dock assets

Built using a combination of AWS technologies including but not limited to YOLO, Kinesis Video Streams, SageMaker, Rekognition, Lambda, S3, IoT Core, DynamoDB, and QuickSight. InventoryView provides real-time tracking, count verification, movement forecasting, and location insights across indoor and outdoor environments.

This solution reduces manual cycle counts, eliminates lost inventory, accelerates order fulfillment, improves material flow, and enhances operational accuracy across diverse industries.

Optional edge inference on NVIDIA Jetson or GPU-enabled gateways supports low-latency processing in large warehouses, industrial plants, construction sites, or remote locations.

• Works with existing CCTV/IP cameras (no extra hardware needed for cloud inference)
• Integrates with RFID, barcodes, GPS, telematics, BLE, UWB, IoT sensors
• Cloud or edge inference using AWS or NVIDIA Jetson
• Integration with WMS, ERP, MES, YMS, TMS
• Dashboards for inventory flow, counts & discrepancies
• Supports warehouses, plants, ports, yards & industrial sites

Inventory Assessment & Workflow Analysis

• Review warehouse/facility layout, SKU types, pick/put workflows, and camera/device ecosystem

Data Pipeline Configuration

• Configure AWS Kinesis Video Streams, IoT Core, S3 for ingesting camera + device data

Model Development & Optimization

• • Models trained/optimized for:
• Pallet detection
• SKU/case detection
• Tool & equipment tracking
• Material placement/movement
• Inbound/outbound verification

• Cloud inference via SageMaker or Rekognition
• Edge inference via NVIDIA Jetson/GPU-enabled gateways

Integration Work

• APIs for WMS/ERP/MES/YMS/Inventory systems
• Optional barcode/RFID/GPS/telematics integrations

Dashboards & Reporting

• Dashboards for movement flow, inventory counts, exceptions & anomalies

Testing & Validation

• Accuracy tuning, lighting/coverage checks, movement pattern validation

Documentation & Knowledge Transfer

• SOPs, architecture documentation & training for inventory teams

• Deployed InventoryView AI pipeline
• Cloud or edge vision inference setup
• Integrated API layer for WMS/ERP/RFID/IoT systems
• Real-time dashboards for inventory flow & tracking
• Exception & discrepancy reporting
• Performance validation report
• Deployment documentation
• Knowledge-transfer workshop

• Provide access to cameras or sample video footage
• Provide AWS environment access or provisioning rights
• Provide integration details for WMS/ERP/MES/YMS/RFID/ IoT/telematics
• Provide SKU/pallet/material details and workflow documentation
• Ensure network connectivity to AWS or edge devices