SpaceX Dragon spacecraft in orbit
Architecture

From satellite to decision in under 60 seconds.

Our four layer pipeline transforms raw satellite measurements into actionable intelligence for European institutions.

The Pipeline
Layer 01

Sensing

Six Sentinel satellite families plus EUMETSAT Meteosat provide optical, radar, thermal, atmospheric, altimetric, and geostationary coverage. All data is sourced from the Copernicus programme, free of charge and governed by EU law.

Layer 02

Fusion

Multiple data streams are atmospherically corrected, geometrically aligned, and merged with contextual data including vessel transponder records, ERA5 atmospheric reanalysis, and infrastructure databases.

Layer 03

Cognitive Models

Foundation models trained on the full Copernicus archive apply causal reasoning, longitudinal memory, and uncertainty quantification to transform fused data into structured intelligence outputs.

Layer 04

Delivery

Ranked actionable outputs with confidence intervals, recommended actions, trajectory forecasts, and full audit trails are delivered to operators and integrated systems in under 60 seconds.

Three Core Properties

Causal Reasoning

We ask why, not just what. When Sentinel-2 data shows a vegetation anomaly, our platform determines whether the cause is drought, disease, or management failure. The appropriate response to each is completely different.

Longitudinal Memory

A single satellite observation carries limited meaning without context. We maintain continuous records across the full Copernicus archive, allowing us to reason about trends, rates of change, and historical baselines.

Epistemic Honesty

Every output carries a calibrated confidence interval. When data gaps or sensor limitations reduce our confidence below operational threshold, we say so explicitly and request additional observations. We do not produce confident outputs when confidence is not warranted.

White satellite dish against blue sky
EU AI Act

Compliant from the first line of code.

Every output carries a trace identifier linking it to the model version, data inputs, confidence calculation, and reasoning chain that produced it. Any output can be audited by a national supervisory authority on request. We built this because it makes a better system, and because the EU AI Act requires it for high risk deployments.

Our platform
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