Empower machines to see, understand, and act with computer vision—enabling real-time safety, analytics, and automation at the edge.
Real-Time Face Mask Detection
- A real-time vision system that detects whether a person is wearing a mask or PPE kit.
- Runs on edge devices for public spaces.
- Alerts or logs violations in real-time for safety compliance.
- Used in healthcare, food and pharmaceutical industries.
Object Detection for Retail Analytics
- YOLO-based retail vision system for identifying items and people in-store.
- Supports CCTV integration with real-time processing.
- Helps retailers optimize store layout and reduce stock-outs.
Protective Gear Detection at Construction Sites
- Detects whether workers are wearing helmets, vests, and boots using AI vision.
- Used on CCTV feeds for safety compliance in real time.
- Alerts supervisors upon detecting violations.
- Deployed on edge devices or central servers.
- Helps reduce on-site accidents and improve compliance.
Material Crack Detection System
- Uses computer vision to find micro and macro cracks.
- Trained on diverse surface datasets under different lighting.
- Used in real-time camera inspection workflows.
- Auto-flags critical damage and estimates crack dimensions.
Material Quality Checker
- Detects deformities, shape irregularities, and defects.
- Works with conveyor belts or handheld cameras on-site.
- AI filters out damaged pieces before packing or use.
- Improves consistency and reduces wastage.
- Supports image classification + object detection hybrid pipeline.
Safety Sign Checker
- Detects presence and correct placement of signs, alarms.
- Used in real estate, offices, and industry to verify safety audits.
- Works with mobile apps or CCTV footage.
- Flags missing or expired safety equipment.
- Used for insurance, construction, and workplace compliance.
Hazard Zone Intrusion Detection
- Identifies people entering restricted or dangerous zones using YOLO-based tracking.
- Supports facial redaction for privacy.
- Auto-sends alerts to site supervisors or mobile apps.
- Supports perimeter monitoring in real-time.
- Deployed in power plants, tunnels, and crane zones.
Security & Surveillance in CCTV Feeds
- Unsupervised learning model to flag unusual behavior or intrusions.
- Uses autoencoders and motion tracking to learn normal patterns.
- Deployed on edge devices for real-time monitoring.
- Alerts security personnel upon detecting anomalies.
- Useful in factories, banks, and restricted zones.