As part of this initiative, the two companies co-developed a new proof-of-concept tool designed to assist operators and engineers in managing the growing complexity of Proliferated Low Earth Orbit (pLEO) constellations—extensive networks of small satellites near Earth that enable faster communication and enhanced global coverage.

As satellite constellations scale from dozens to hundreds or even thousands of assets, space system operators are faced with high-volume, high-velocity data that can leave critical signals lost in the noise. Current standard processes often require engineers to rotate between separate screens to monitor bus telemetry, payload status and ground network availability. When an anomaly occurs, on-call engineers typically spend critical minutes manually correlating data to determine if an alarm is a genuine threat.

To solve this, Aerospace collaborated with Google Public Sector’s Rapid Innovation Team to create a tool, leveraging Google Cloud’s Vertex AI platform, that acts as a force multiplier to automatically monitor the status of every satellite to detect behavioral anomalies. By fusing disparate telemetry streams into a single, intelligent interface, this system moves beyond static threshold alarms toward predictive behavioral monitoring.

“This concept demonstrates how AI can be a critical operational partner capable of handling the high-velocity demands of modern space domain awareness, helping on-call engineers focus their expertise where it matters most,” said Kevin Bell, senior vice president of Aerospace’s Engineering and Technology Group. “Collaborations like this are an important part of Aerospace’s ongoing work to build connections with industry and accelerate the adoption of innovative technologies to support national priorities in space.”

The proof-of-concept tool is specifically designed to support on-call engineers and operators by transforming how data is integrated and how anomalies are triaged. The AI-based solution would augment passive monitoring with active, machine learning insights, detecting subtle behavioral anomalies—such as a momentum wheel oscillating only when a specific payload is active—that otherwise go unnoticed until a component failure occurs. The tool can instantly correlate anomalies with relevant contexts—such as recent payload tasks or space weather events—and present an analysis of potential root causes.

“We are proud to collaborate with The Aerospace Corporation to bring Google’s AI to the final frontier,” said Cameron Groves, director of Rapid Innovation & Specialist Engineering at Google Public Sector. “This pathfinding effort demonstrates that by equipping engineers with the right data at the right time, we can help transform the operator experience from reactive firefighting to proactive problem-solving to accelerate operations. We look forward to seeing this transition from a concept into operational use.”