Sentinel Capability

AI Threat Detection

Own The Edge

Advanced computer vision identifies humans, vehicles, and anomalies with 99.2% accuracy. The system distinguishes between wildlife and actual threats, minimizing false alarms while ensuring no intrusion goes undetected. Continuous learning improves detection over time.

AI Threat Detection

Missions

Human Detection

Identify and track individuals across your property with high accuracy, distinguishing between authorized personnel and potential intruders.

Vehicle Recognition

Detect and classify vehicles by type, tracking their movement patterns and alerting on unauthorized access attempts.

Anomaly Detection

AI identifies unusual patterns and behaviors that may indicate security threats, from fence tampering to suspicious loitering.

99.2%Detection Accuracy

Industry-leading accuracy achieved through deep learning models trained on diverse security scenarios.

<100msProcessing Time

Real-time detection with sub-100 millisecond latency from image capture to alert generation.

95%False Alarm Reduction

Intelligent filtering dramatically reduces nuisance alerts from wildlife and environmental factors.

24/7Continuous Learning

AI models improve continuously, adapting to your specific environment and threat patterns.

Computer Vision[01]

Deep Learning Models

Neural networks trained on millions of security scenarios achieve 99.2% detection accuracy. The system continuously learns from new data, improving performance over time and adapting to your specific environment.

Deep Learning Models
Computer Vision[02]

False Alarm Reduction

Intelligent filtering distinguishes between actual threats and harmless triggers like wildlife, shadows, and environmental movement. Reduce false alarm rates by up to 95% compared to traditional motion detection.

False Alarm Reduction
Computer Vision[03]

Object Classification

Beyond simple detection, the AI classifies objects by type — person, vehicle, animal, or object. Receive specific alerts with context, enabling faster and more appropriate response decisions.

Object Classification
Computer Vision[04]

Behavior Analysis

Track movement patterns and identify suspicious behaviors like loitering, fence-line following, or repeated access attempts. Proactive alerts before a breach occurs.