NEXT-GEN RETAIL LOSS PREVENTION

Stop Shoplifting in Real-Time with Behavior-Based AI

Fire Shoplifting & Loss Prevention

The Challenges We Solve

 Shoplifting detection

Key Features of  Shoplifting Detection

Leveraging advanced pose estimation and spatial-temporal graphs, TensorVok AI instantly detects suspicious body movements associated with shoplifting. The algorithm monitors deep interactions between a shopper’s hands, clothing, and high-risk merchandise, automatically flagging behaviors like slipping products into pockets, waistbands, or personal bags. By alerting store staff within seconds of the suspicious action, retailers can execute soft interventions on the sales floor well before the shoplifter reaches the exit.

shoplifting
Real-Time Concealment Recognition

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 fire smoke detection

The AI Ecosystem Integration

Sense (Video AI)

TensorVok utilizes high-performance computer vision pipelines to analyze raw video data at the edge in real-time. By leveraging advanced pose estimation, spatial-temporal graphs, and multi-object tracking (MOT), the system transforms standard CCTV/NVR networks into intelligent sensory nodes. It continuously scans the retail environment to accurately detect specific behavioral anomalies—such as merchandise concealment or self-checkout scan avoidance—without extracting biometric features, ensuring a privacy-first sensing layer.

Think (AI Agent)

At the core of our ecosystem, the TensorVok AI Agent functions as the cognitive decision engine. It cross-references the behavioral anomalies flagged by the Video AI with real-time POS transaction logs and contextual store data. The agent evaluates the sequential intent of the shopper, filters out normal consumer actions (like reading a label and returning a product), and instantly validates whether an event constitutes high-probability theft, drastically minimizing false positives before escalating the event.

Act (AIoT)

Once a shoplifting or checkout threat is validated, TensorVok triggers immediate, automated workflows through localized AIoT integration. The system dispatches real-time push alerts with precise bounding-box snapshots directly to store associates’ mobile apps, handheld PDA devices, or smartwatches, allowing for immediate, soft floor interventions. Simultaneously, it can interface with smart gate systems, digital signage, or electronic article surveillance (EAS) hubs to proactively secure high-value retail zones.

shoplifting detection

Application Scenarios

Smart Self-Checkout (SCO) Lanes

High-Value Merchandise Aisles

Checkout Gate Pushout Prevention

Blind Spots & Concealment Zones

After-Hours & Flash Mob Crowd Alerts

Smart Warehouse & Backroom Inventory Security

Our Value

Saving Assets and Reducing Insurance Premiums.

Compliance & ROI

Fires are the single greatest threat to business continuity. In Singapore, fire safety compliance is strictly audited. TensorVok doesn’t just meet these standards; it exceeds them by providing “pre-incident” detection.

By reducing response time from minutes to seconds, you minimize property damage and avoid total operational shutdown. Many insurers also offer lower premiums for facilities equipped with advanced AI fire detection systems.

Check WSH regulations of Singapore

100% Audit-Ready

Reduce Fines

98% Accuracy

F.A.Q.

Find answers to commonly asked questions about our services and trading strategies

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