S

Silent Vision

Catch What They Don’t Scan — in Real Time

Self-checkout (SCO) is efficient for customers — and enticing for fraud. Silent Vision's Self-Checkout Fraud Detection solution uses AI-powered video analytics to monitor SCO stations and flag fraudulent behavior like item skipping, barcode switching, and unauthorized bagging in real time.
Woman in medical mask pays at self-checkouts.

🔍 What We Help You Detect

Grocery Store Checkout Process During Pandemic

🎯 Unscanned Item Theft

Detect when an item bypasses the scanner — whether placed directly in a bag, under another item, or walked past without interaction.

A woman's hands are shown scanning a box of spaghetti at the grocery store's self-checkout service.

🔄 Barcode Switching / Tag Swapping

Flag price fraud when a lower-value item is scanned in place of a high-value one, or labels are switched between products.

Woman pays at self-checkouts in supermarket.

🧺 Improper Bagging Behavior

Identify attempts to conceal items, use bags before scanning, or manipulate system bagging prompts (e.g., pressing “Own Bag” then bagging items).

Business Outcomes

Business Outcomes

  •  Reduce SCO shrink by 20–40% with real-time detection
  • Save review time with automated video clips of flagged incidents
  •  Use visual data to train employees or deter theft
  • Maintain customer convenience without increasing friction
🛠 How It Works

🛠 How It Works

  • Cameras positioned above or beside SCO stations
  • AI action recognition + ROI-based event triggers
  • Optional ReID tracks repeat fraud attempts
  • Edge inference on Jetson Orin or
  • Cloud GPU Webhook alerting to dashboards, apps, or security staff

Powered By:

  • Self-Checkout Fraud Detection AI
  • Action Recognition + ReID
  • Vision Showcase
  • Heatmaps & Zone Analytics