LunaVIs deploys GPU-accelerated computer vision models for physical operations. We combine custom object detection, instance segmentation, and deep learning pipelines (NVIDIA TensorRT / DeepStream) to automate retail footfall analysis, monitor HSE PPE compliance, streamline FR time attendance, and manage secure facilities with ANPR telemetry.
Track customer journeys across non-overlapping camera feeds. Our deep feature extraction models maintain persistent identity tracking even across entrances, floors, and occlusions.
Leverage Facial Recognition (FR) analytics for secure access control and time-attendance logging. Detect and verify authorized personnel in millisecond inference times.
Enforce workplace safety rules with real-time PPE detection. Our instance segmentation models detect hard hats, safety vests, and protective gear, logging violations instantly.
Automate gate entries and traffic logging using Automatic Number Plate Recognition (ANPR). Detect, recognize, and log license plates to integrate with your existing access systems.
Conduct footfall analysis retail audits automatically. Track dwell times per aisle and zone to optimize product placements, layouts, and staffing levels based on spatial analytics.
Secure perimeters with real-time zone intrusion alerting. Instantly classify anomalies and send context-rich alerts directly to team channels, reducing false alarms.
Built on NVIDIA TensorRT and DeepStream for ~30ms real-time latency. Object detection via YOLOv8 and InsightFace for face feature extraction. Runs on your own computer on-site; our team sets it up remotely.
Early Access is open for retail, security, and industrial deployments across the UAE, Saudi Arabia, Egypt, Jordan, Pakistan, Singapore, India and the Philippines.
Request Early Access