Real-time anomaly detection for complex, multi-sensor environments. Physics-based. Training-data-free. Edge-deployable.
Get in TouchA fundamentally different way to find anomalies in sensor data — no training sets, no labeled data, no retraining cycles.
Works from first principles using physics-based statistical signatures. No pre-collected training datasets required — effective from day one against novel targets.
K=6 independent statistical probes analyze every sensor tile simultaneously. Redundant, orthogonal detection channels minimize false negatives and false positives.
Anomaly detection and classification in a single pass. The engine doesn't just find anomalies — it categorizes and prioritizes them in real-time.
Native ingestion of EO/IR, Radar, RF, Acoustic, ADS-B, and Remote ID. Correlated detections across modalities reduce ambiguity and increase confidence.
Benchmarked on multi-modal sensor sequences with full tracking pipeline.
Multi-target tracking with automatic lifecycle management — birth, update, coast, and termination handled seamlessly.
Ranked alert feeds with time-to-zone estimation. Operators see the most critical threats first with evidence packages.
Designed for NVIDIA Jetson deployment. Compact enough for forward-deployed nodes, powerful enough for multi-sensor fusion.
From strategic intelligence to fused operator picture — a complete detection pipeline.
Threat landscape awareness from open-source intelligence feeds
Multi-sensor ingestion at the tactical edge
Stochastic anomaly analysis with classification
Correlated, prioritized operator feed with evidence
Ready to see what stochastic anomaly detection can do for your environment? Let's talk.
info@anomalies.us