Karthikeyan Natarajan@karthi

Autonomous robots and AI agents are becoming increasingly common in warehouses, hospitals, construction sites, and public spaces. Yet most systems allow these agents to act freely, with no real-time oversight layer between intent and execution. SafeGuard Sentinel solves this. SafeGuard Sentinel is an AI governance layer that intercepts every proposed robot action before it executes. Using YOLOv8 computer vision, it analyzes the live environment to detect humans and obstacles. A rule-based safety policy engine then evaluates the action against 8 safety rules checking human proximity, speed limits, zone boundaries, and fleet-wide conflict and assigns a risk score from 0 to 100%. Every decision returns one of three verdicts: ALLOW, WARN, or BLOCK. An optional LLM reasoning layer then generates a plain-English explanation of why the decision was made, making the system fully explainable and auditable. Three advanced features make SafeGuard Sentinel production-realistic. Zone Mapping lets operators define restricted, warning, and safe areas directly on the camera feed actions near restricted zones automatically receive elevated risk scores. Multi-Robot Fleet Management tracks multiple agents simultaneously, with fleet-level rules that pause all movement when multiple robots are blocked. The Human Override Panel allows authorized operators to challenge any blocked action within a 2-minute window, with mandatory justification logged to a permanent audit trail. SafeGuard Sentinel demonstrates that autonomous systems don't have to choose between capability and safety. With the right governance layer, every action can be fast, explainable, and human-supervised.

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