AI-Powered Loss Prevention Architecture
In-store video surveillance is essential for shoplifting prevention. Discover our software, which detects shoplifting incidents automatically in real-time.
45%
Reduction in shrinkage
120+
Stores deployed
<200ms
Incident detection time
$5.4M
Annual savings
45% reduction in shrinkage within the first 6 months of deployment.
The Challenge
A major retail chain with 120+ stores across Canada faced an estimated $12M annual shrinkage problem. Traditional CCTV systems required enormous manpower to review footage and could only report incidents after the fact, making real-time prevention impossible.
Our Approach
We architected a real-time computer vision platform built on edge-computing nodes installed directly in each store. The system uses advanced convolutional neural networks (CNNs) trained on proprietary shoplifting behavior datasets to identify and flag suspicious activity within milliseconds — sending instant alerts to loss prevention staff without requiring central cloud processing.
The Impact
Beyond the direct 45% reduction in shrinkage, the platform freed up over 2,000 hours per month previously spent reviewing CCTV footage, allowing loss prevention teams to focus on proactive strategies. The client also saw a dramatic improvement in store morale and customer experience as incidents were handled more discretely and effectively.
Project Timeline
Data Audit & Model Training
Collected 6 months of historical CCTV footage. Labeled and trained initial detection models on over 50,000 annotated shoplifting events.
Edge Infrastructure Deployment
Installed edge computing nodes across 120 stores without disrupting daily operations. Integrated with existing CCTV hardware.
Real-time Monitoring & Optimization
Activated live alerting. Ran a continuous feedback loop to retrain models monthly, improving accuracy from 87% to 97%.
"This system transformed how we think about loss prevention. We went from reactive to truly proactive almost overnight."
Michael Chen
VP of Operations
National Retail Group
Technologies & Domains
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