Structural anomaly detection in radio frequency channels and astrophysical signals. Validated against real data from NASA and the Green Bank Telescope, outperforming the ESA standard tool on transient event detection and explainability.
Solutions in this category
Each solution targets a specific signal type within space signals. All share the same white-box, physics-based foundation.
RF channels · Signal classification
Classifies radio frequency channels automatically, detecting and categorising interference (RFI) without human intervention. Validated on 9 independent Green Bank Telescope observations (315,392 channels per observation). Outperforms the ESA standard tool (AOFlagger) on transient event detection and explainability.
Coverage
Transient events · Space signals
Detects transient anomalies in astrophysical signals that no conventional spectral analysis method can see. Validated on real data from the NASA Parker Solar Probe: theoretical prediction confirmed at 0.2σ across 4,649 independent intervals, with zero free parameters.
Coverage
Who it's for
Every result is fully transparent and auditable. Every signal can be justified to a regulator.
Grounded in statistical physics and stochastic analysis. Structural patterns, not empirical correlations.
Works across assets and time periods without constant retuning or manual adjustment.
Compatible with MiFID II, EU AI Act, Basel III and MGA from day one.
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