Loading…
Loading…
Defend critical facilities with AI-powered perimeter surveillance that detects intrusion attempts, classifies threats, and eliminates false alarms. Visylix transforms perimeter cameras into intelligent sensors that distinguish humans and vehicles from animals, shadows, and environmental noise.
Key challenges that organizations face without intelligent AI-powered solutions.
Traditional motion-based perimeter detection generates excessive false alarms from wildlife, weather, vegetation movement, and lighting changes, causing alert fatigue and missed genuine threats.
Large perimeters spanning kilometers of fence line require extensive camera coverage that overwhelms human monitoring capacity in security operations centers.
Night-time and adverse weather conditions significantly degrade conventional detection performance precisely when perimeter security is most critical.
Coordinating security response to intrusion events requires precise location identification, threat classification, and visual verification that basic motion alerts cannot provide.
Intelligent capabilities that transform your existing camera infrastructure into a powerful decision-making engine.
Deep learning models distinguish between humans, vehicles, and animals approaching perimeter zones, dramatically reducing false alarms while maintaining detection sensitivity for genuine security threats.
Configurable virtual perimeter zones, directional tripwires, and exclusion areas provide flexible detection boundaries that adapt to complex facility layouts without requiring physical sensor infrastructure.
AI models trained on diverse environmental conditions maintain high detection accuracy through rain, fog, snow, darkness, and challenging lighting scenarios that defeat conventional motion detection.
Per-camera tracking follows detected intruders along the perimeter, providing security teams with real-time position updates, predicted movement paths, and coordinated PTZ camera slew-to-target capability.
Quantifiable improvements delivered through AI-powered intelligence and automation.
AI classification eliminates the vast majority of nuisance alarms from animals, weather, and environmental factors.
Deep learning perimeter analytics achieve near-perfect threat detection rates across all lighting and weather conditions.
Automated threat classification and tracking dramatically reduce the time from detection to coordinated security response.
AI-powered analytics enable each operator to effectively monitor three times more perimeter area than manual surveillance.
It works purely from video on cameras you already have, so there is no additional hardware to install along the fence line. It also distinguishes humans, vehicles and animals, which is what removes the majority of the false alarms that make traditional perimeter sensors get ignored.
Fewer than a fixed-rule system, because the per-camera anomaly model learns what normal looks like for each view and refreshes weekly, and tamper detection builds its own baseline. Visylix does not publish a false-positive reduction percentage, because that depends entirely on your scenes and there is no measurement to support a number.
Yes. Sudarshan rules support scheduling alongside AND/OR conditions and ordered temporal sequences, so a loading bay can be unrestricted during shifts and alarmed overnight. Rules can be dry-run against historical footage before going live.
Edge deployment runs recording and analytics locally, with only alerts and metadata travelling back. SRT and RIST add packet-loss recovery over cellular or long-haul links, so detection does not stop when the link degrades.
Yes, through 200+ REST API endpoints, HMAC-signed webhooks and MQTT for SCADA and IoT. Alerts notify your systems; Visylix does not directly actuate gates, sirens or locks.
Learn how Visylix AI can strengthen your perimeter security with intelligent intrusion detection, false alarm elimination, and coordinated threat response.