RBtec Launches RaySense AI Detection with Offline Operation

Israeli perimeter security specialist RBtec has released RaySense, an AI-powered detection system offering 3-metre pinpoint accuracy for fence-mounted and buried sensor applications. The system runs entirely offline — no cloud connectivity, no subscription fees — with AI classification performed at the edge.

RBtec emphasises the offline-first architecture as a differentiator for military, government, and critical infrastructure sites where cloud dependency introduces both latency and cybersecurity risk. The AI engine classifies intrusion events (climbing, cutting, digging) and suppresses nuisance alarms from environmental sources without transmitting sensor data off-site.

RBtec reports over 5,000 systems deployed across 54 countries, with a customer base concentrated in government, military, and energy infrastructure. The company is headquartered in Israel and competes in the fence-mounted sensor segment alongside Southwest Microwave (MicroPoint), Senstar (FlexZone), Gallagher (Z10), and CIAS (SIOUX PRO2).

The RaySense launch adds to the growing list of PIDS vendors incorporating edge AI into fence sensor products — a category where traditional signal processing (frequency analysis, threshold tuning) has been the standard approach for decades. The shift to machine learning classification promises better nuisance alarm management, but field validation across diverse fence types and environmental conditions will determine whether the AI advantage holds in practice.