Retail Surveillance System
Turn existing IP/CCTV camera feeds into actionable analytics. Upgrade your retail store video surveillance into an Edge AI system for loss prevention, inventory tracking, and heatmaps.
Computer Vision ROI Estimator
Retail ModeCalculate Your Shrinkage Savings
See exactly how fast our Loss Prevention AI models will pay for themselves based on your current store footprint and shrinkage metrics.
Launch the ROI EstimatorTest Live Retail Theft & Concealment Detection
Experience our edge YOLO11-Pose model in action. Switch between sample store camera feeds or upload your own video to test real-time shoplifting detection, pocketing heuristics, and automated incident evidence logging.
Upgrade Your Retail CCTV Security Systems
Legacy retail CCTV security systems generate vast amounts of passive RTSP streams. By integrating our Edge AI gateways directly into your existing IP camera infrastructure, we transform raw video streams into structural, real-time telemetry.
Our models run on-premise, evaluating IP/CCTV camera feeds continuously. The system identifies anomalies (shrinkage events, out-of-stock items) and dispatches actionable payload data to loss prevention and operations teams in real-time.
- Privacy-First Architecture: Analytics rely on spatial geometry and behavioral heuristics rather than facial identity processing, guaranteeing compliance with biometric privacy mandates.
- Low-Bandwidth Edge AI: Inference runs locally on the gateway. Only lightweight JSON alert payloads are transmitted externally, preserving site network bandwidth.
Retail Surveillance System Analytics
Automated Loss Prevention
Detect self-checkout scan avoidance, ticket switching, and shelf-sweeping in real-time, sending immediate alerts to on-duty loss prevention officers.
Customer Footfall Analytics
Generate high-fidelity heatmaps showing exactly how customers navigate your store, allowing you to optimize endcap pricing and product placement.
Automated Shelf Monitoring
Identify out-of-stock items, misplaced products, and planogram compliance failures instantly to ensure maximum sales velocity.
Retail Loss Prevention & Analytics: Architecture Comparison
Evaluate sensor placement, real-time compute load, occlusion resistance, shopper privacy, and CAPEX across retail vision models.
| Retail Tech Architecture | Ceiling Multi-Camera Tracking (Autonomous Checkout) | Smart Shelf Sensor Fusion (Weight + Micro-Cameras) | Point-of-Sale AI Vision (Anti-Sweethearting) |
|---|---|---|---|
| Shopper Journey Tracking | Continuous 3D multi-camera re-identification (ReID) mapping shopper paths, dwell times, and basket interactions. | Detects SKU removal/return at specific shelf bins via load cells and planar optical sensors. | Focuses strictly on the checkout bagging and scanner area; verifies item scanned matches item placed. |
| Occlusion & Crowd Density | Vulnerable to extreme store crowding, overlapping bodies, and tall fixtures without dense camera grids. | Zero optical occlusion vulnerability; physical weight changes trigger detection regardless of crowd density. | Isolated, controlled optical field-of-view; minimal occlusion interference from neighboring shoppers. |
| Store Retrofit CAPEX | High capital expenditure; requires ceiling structural grids, tens of PoE cameras, and high-wattage edge GPU servers. | Moderate CAPEX; requires specialized modular shelf retrofitting, power distribution, and load cell calibration. | Low CAPEX; easily retrofitted to existing POS registers via single downward-angled overhead camera. |
| Shrinkage & Theft Prevention | Prevents walk-out shrinkage; accurately links SKU interactions to shopper virtual baskets. | Flags stock depletion, misplaced items, and shelf sweep theft events in real time. | Eliminates barcode swapping, missed scans, ticket switching, and employee sweethearting fraud. |
| Shopper Privacy (GDPR/CCPA) | High regulatory scrutiny; requires facial blurring, skeleton keypoint tracking, and zero biometric persistence. | Zero biometric exposure; tracks weight delta and mechanical shelf movement without capturing customer faces. | Limited exposure; captures hands and item barcodes strictly in transactional checkout zone. |
| Best-Fit Retail Format | Compact convenience stores, grab-and-go airport kiosks, micro-markets, and frictionless stores. | High-value beauty, cosmetics, luxury consumer electronics, and high-theft pharmacy retail aisles. | Supermarkets, big-box department stores, wholesale clubs, and standard franchise retail cash wraps. |
Frequently Asked Questions
Can we use our existing store security cameras?
Yes. Our Edge AI gateway connects directly to your existing IP camera network via RTSP streams. You do not need to rip and replace your entire CCTV infrastructure to deploy our retail vision models.
How does AI detect shoplifting without facial recognition?
Our loss prevention models focus entirely on behavioral analytics (e.g., detecting the specific motion of a hand hiding an item in a bag or jacket) rather than facial identity. This ensures full compliance with GDPR and state privacy laws.
What is the typical ROI for retail computer vision?
For enterprise retailers, reducing inventory shrinkage by just 10% often pays for the entire CV deployment within 6 months. Additionally, heatmapping data allows for optimized product placement, directly increasing average cart value.
Stop Inventory Shrinkage
Secure your margins with advanced AI loss prevention. Talk to our retail engineering team today.
Request a Store AuditTalk Directly to a Vision Architect
Book a zero-pitch scoping session to discuss camera feeds, heatmaps, and POS integration.
Book a 20-Min Technical Strategy Call
Discuss your architecture, feasibility, hardware sizing, or custom software requirements directly with a senior engineer.
You're on Our Calendar!
We have registered your session. A calendar invite (.ics) and meeting details have been emailed to .
20 Mins • Google Meet / Conference