Physics-based anomaly detection for critical infrastructure and security operations. Heimdall Sentry detects unusual patterns through sensor fusion and transparent evidence-based analysis.
Heimdall Sentry identifies anomalous patterns in environments where baseline behavior is known and deviations matter. The system evaluates patterns, not classifications.
Detects regular, repeating behaviors that deviate from established environmental baselines. Uses physics-informed models rather than signature matching.
Evaluates signal duration and consistency over time. Sustained patterns receive higher confidence than transient anomalies.
Correlates data across independent sensor types (acoustic, RF, visual, thermal). Agreement between sensors reduces false positives substantially.
Heimdall provides transparent, explainable detections with quantified confidence and supporting evidence.
Probabilistic assessment based on measured signal characteristics. Operators understand the strength of evidence behind each detection.
Every detection includes supporting data: which sensors contributed, baseline comparison, and pattern metrics. Fully auditable.
Alexandria stores historical patterns and outcomes. The system learns from operator feedback and improves over time.
Monitor facilities, perimeters, and sensitive areas for unusual activity patterns. Integrates with existing security systems and provides early warning of potential threats.
Detect and track low-altitude activity using acoustic and RF sensor arrays. Provides persistent coverage in areas where radar coverage is limited or unavailable.
Temporary deployments for high-profile events or facilities. Quick setup, sensor fusion across multiple modalities, and real-time alerting for security teams.
Forward operating base security and mobile convoy protection. Edge-deployable for disconnected or bandwidth-limited environments.
Heimdall Sentry adapts to your infrastructure and security requirements.
Run processing directly on sensor nodes or local gateways. Low latency, no cloud dependency, suitable for classified or disconnected environments.
Centralized analysis for distributed sensor networks. Leverages Alexandria's memory layer for cross-site correlation and historical pattern matching.
Edge processing for immediate alerts, cloud correlation for intelligence. Best of both worlds for large or distributed deployments.
Qualified stakeholders may request detailed technical briefings for deployment evaluation, integration planning, or research collaboration.
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