AI-Powered Loss Prevention Architecture
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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

1,200+

International locations

<200ms

Incident detection time

$54M

Annual savings

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Key Result

45% reduction in shrinkage within the first 6 months of deployment.

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The Challenge

A global retail leader with 1,200+ multinational locations faced an estimated $120M annual shrinkage problem across its international operations. Traditional CCTV systems required enormous manpower to review footage and could only report incidents after the fact, making real-time prevention impossible at this scale.

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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.

Shrinkage Rate Reduction Post-Deployment

Source: Stigma Technologies Analytics Internal Data

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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

1
Phase 1

Data Audit & Model Training

Collected 6 months of historical CCTV footage. Labeled and trained initial detection models on over 50,000 annotated shoplifting events.

2
Phase 2

Edge Infrastructure Deployment

Deployed edge computing nodes across 1,200 locations worldwide without disrupting daily operations. Integrated with existing global CCTV hardware.

3
Phase 3

Real-time Monitoring & Optimization

Activated live alerting. Ran a continuous feedback loop to retrain models monthly, improving accuracy from 87% to 97%.

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"This system transformed how we think about loss prevention. We went from reactive to truly proactive almost overnight."

Michael Chen

Global VP of Operations @ Global Retail Operations

CORE_TECHNOLOGIES

AI / MLComputer VisionEdge ComputingRetail

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Phone

+1 855-552-1005

mail

Email

contact@stigmatech.ca

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Global Headquarters

6205, Blvd des Grandes-Prairies, St-Léonard, QC, H1P1A5