Heimdall operates like a detective, not a black box. It establishes baselines, identifies deviations, builds evidence, and maintains institutional memory. This approach works across security, environmental, and research domains.
Observe normal patterns continuously. Learn what "expected" looks like in your specific environment. Baseline models adapt over time as conditions change.
Detect when signals differ from established baselines using physics-informed models. Quantify confidence based on magnitude, persistence, and cross-sensor agreement.
Store detections with full context in Alexandria. Build institutional knowledge that improves accuracy and provides audit trails for every decision.
Three core components work together to turn raw sensor data into actionable intelligence.
The Anomaly Detection Engine
Heimdall analyzes raw sensor streams to identify patterns that deviate from established baselines. It uses physics-informed models tailored to each domain (acoustic propagation for security, thermal dynamics for wildfire, cellular mechanics for medical research).
Key Capabilities:
The Institutional Memory Layer
Alexandria stores signal signatures, detection events, and operator feedback. This creates a knowledge base that enables pattern matching, historical correlation, and continuous learning.
Key Capabilities:
The Operational Interface
Northlight presents detections, confidence scores, and supporting evidence in a form designed for human decision-makers. It's not just alerts—it's context, history, and explanation.
Key Capabilities:
These principles guide how the platform is built and operates across all domains.
Every detection includes explainable confidence scores and evidence. Operators understand why something was flagged, not just that it was flagged.
Detection algorithms are grounded in physical principles (acoustic propagation, RF behavior, thermal dynamics) rather than pure statistical pattern matching.
The platform works with diverse sensor types and manufacturers. No vendor lock-in. Bring your own sensors or use our recommended configurations.
Heimdall assists decision-makers, it doesn't replace them. High-consequence decisions require human judgment informed by good intelligence.
Every detection builds knowledge. The system learns from operator feedback and improves over time while maintaining full audit trails.
Data sovereignty, air-gap deployment options, and compliance support are built in from the start, not added later.
The same core platform applies to different problem domains by changing sensors, baseline models, and evaluation criteria.
Sensors: Acoustic arrays, RF monitoring, visual/thermal cameras
Baseline: Normal site activity patterns, ambient noise, RF environment
Deviations: Unusual acoustic signatures, RF emissions, movement patterns
Output: Confidence-scored alerts with sensor fusion evidence
Sensors: Satellite thermal imagery, ground sensors, weather data
Baseline: Seasonal fire behavior, environmental conditions, historical patterns
Deviations: Thermal anomalies, rapid spread indicators, escalation signals
Output: Early warning with predicted spread and confidence scoring
Sensors: Acoustic transducers (experimental)
Baseline: Known cell line mechanical properties from literature
Deviations: Cellular populations with anomalous acoustic signatures
Output: Research-only visualizations (not diagnostic)
Try our interactive demos or contact us for a technical briefing on deployment options.
Try Security Demo Request Briefing