RadiGuard leverages AI and machine learning algorithms to analyze data from advanced in-situ sensors placed on spacecraft components most vulnerable to radiation.

These sensors provide high granularity data, detecting micro-fluctuations in component behavior that indicate early-stage damage.

The AI system processes this data to predict any progressive degradation patterns, enabling operators to schedule timely maintenance.

It integrates seamlessly with existing satellite telemetry systems and offers a user-friendly dashboard for real-time monitoring and alerts.

RadiGuard provides unprecedented diagnostic precision, enabling operators to preemptively address issues before they develop into critical failures.

It reduces the risk of mission loss and extends the operational lifespan of satellites, offering significant cost savings over the satellite lifecycle and potentially lower insurance premiums.

The system's AI-driven insights allow for informed decision-making, enhancing mission confidence and performance.

Technologically, AI-driven analytics are mature enough to interpret vast datasets for predictive outcomes, and sensors capable of withstanding radiation are available but may require custom integration.

Business-wise, the demand is present among operators looking to reduce unscheduled downtimes and extend satellite lifecycles.

Regulatory aspects are manageable given the Eurozone's supportive environment for satellite innovations.