Our Approach
Our Approach
Most tools help you see more.
We help you look at less.
The missing layer in satellite operations.
Decision architecture, not alerting.
As satellite fleets grow, the problem isn't data. It's the cognitive load of turning data into decisions — shift after shift, across more spacecraft, with the same team.
We build systems that do that work.
AI anomaly detectors are good at finding deviations. They're not designed to tell you which ones matter.
We validated this against 14 years of real mission data using the ESA Anomaly Detection Benchmark. Our AI layer achieved a ROC-AUC of 0.936 — strong performance by any standard.
And yet, even at that level, standalone detection generates a continuous stream of false escalations that land on operators as uninvestigated noise.
Detection accuracy is not the bottleneck. Operational relevance is.
Our approach combines AI scoring with deterministic reasoning — mission context, spacecraft state, scheduled activities, cross-parameter conditions — to determine what actually requires attention.
What reaches the operator isn't a score. It's a decision-ready event: context attached, history surfaced, response suggested, authority preserved.
The same team. Managing twice the complexity. With the same confidence.