AI for Retail Shrinkage Detection

Detect theft, fraud, and process losses using computer vision, sensors, and analytics across stores and distribution.

Shrinkage erodes margins through theft, fraud, and operational errors. AI-driven CV, sensors, and data fusion can detect events in real time, flag anomalies, and reduce losses while respecting privacy and store experience.

Cold-chain and asset tracking in back rooms.

POS anomaly detection; returns/refunds fraud.

Inventory reconciliation between WMS/POS; phantom inventory.

live demo · related simulation● LIVE

Edge CV inference; privacy masks; on-site buffering.

Sensor gateways; POS/WMS connectors.

Event bus for real-time signals.

Frequently asked questions

What is the Implementation Roadmap for mysimulator.uk?

Implementation Roadmap

What is the recommended approach to begin using mysimulator.uk, focusing on high-shrink stores and SKUs, and deployment strategies?

Start with high-shrink stores/SKUs; depl?

How can I enable exit monitoring and receipt reconciliation within the system, and what adjustments should be made to the associated thresholds?

Enable exit monitoring and receipt reconciliation; tune thresholds.

Where should I deploy RFID or weight sensors to maximize return on investment (ROI)?

Add RFID/weight sensors where ROI is highest.

▶ Try it live

Everything above runs in your browser — open Hash Function Avalanche Visualizer and change the parameters while it is running. Nothing is installed, nothing is uploaded, the whole model lives in one tab.

▶ Open Hash Function Avalanche Visualizer simulation