Visenty: Retail Security Platform

Visenty is an AI-powered retail security platform designed to detect and prevent shoplifting in real-time. Combining advanced computer vision, facial recognition, and behavioral analysis, Visenty provides retail stores with intelligent surveillance and alerts to protect inventory and improve security operations.

In Action

Visenty real-time dashboard monitoring multiple camera feeds and events Visenty mobile app onboarding and QR code setup screen

Key Features

  • Real-Time Shoplifting Detection: AI-powered analysis detects suspicious behavior patterns
  • Facial Recognition: Identifies known offenders and tracks repeat incidents
  • Instant Alerts: Immediate notifications to security staff when threats detected
  • Analytics Dashboard: Comprehensive data on incidents, trends, and hotspots
  • Mobile Companion App: Monitor security events on iOS and Android devices (on App Store)
  • Behavioral Analysis: Tracks movement patterns and predicts potential incidents

Technology Stack

Backend & AI

  • AI Model: Gate Flow SlowFast 3D CNN for behavioral analysis
  • Face Recognition: Deep learning-based identity matching
  • Video Processing: Real-time frame analysis with OpenCV
  • Server: Python Flask backend with multi-camera support

Frontend & Mobile

  • Web Interface: Real-time monitoring dashboard
  • Mobile App: React Native (iOS & Android)
  • Push Notifications: Instant alerts to store managers
  • Design System: Modern, minimal UI with dark mode

Infrastructure

  • Multi-Camera Support: Handle multiple camera feeds simultaneously
  • Database: Persistent storage of incidents and offender profiles
  • API: RESTful API for third-party integrations

How It Works

Detection Pipeline

  1. Video Capture: Real-time camera feed processing
  2. Person Detection: Identify individuals in the frame
  3. Tracking: Follow subjects across camera views
  4. Face Recognition: Match against known offender database
  5. Behavioral Analysis: Apply 3D CNN model to motion sequences
  6. Alert Generation: Trigger notifications if shoplifting behavior detected

Confidence Thresholds

  • Detection requires 64 frames of data (~2 seconds at 30fps)
  • Default confidence threshold: 70%
  • Configurable thresholds for different environments

Open Source Repositories

Impact

  • Real-time threat detection reduces response time significantly
  • Facial recognition integration improves offender identification
  • Multi-store support enables centralized security management
  • Mobile alerts keep managers informed 24/7
  • Data analytics help identify vulnerable areas and patterns

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