Accelerate data processing for space operations
ARC uses machine learning (ML) to process large volumes of photometric and astrometric data to generate actionable insights that improve mission planning, threat detection, and decision-making on orbit.
Analysts are overwhelmed by large volumes of unprocessed data
Space is more congested and contested than ever before. The number of resident space objects (RSOs) and the volume of raw optical sensor data is increasing exponentially. Meanwhile, our ability to process all of this data is falling behind.
ARC is an analytics toolbox that processes large volumes of data quickly with machine learning
ARC processes large volumes of data and surfaces high priority insights to human analysts. Through applied machine learning, ARC can surface insights from existing datasets that may otherwise go undetected.
What you can do with ARC
ARC's algorithms detect patterns in data and behavior that can be used to classify objects or alert human analysts to suspicious maneuvers.
01
Classify objects
ARC accurately characterizes rsos as active payloads, inactive payloads, or debris.
02
Detect anomalies
Algorithms can detect behavior outside the pattern of life for high priority objects.
03
Respond to alerts
ARC surfaces key insights via alerts, so that operators can prioritize downstream operations.
Customize your ARC package to your needs
Unlike closed protocol alternatives, the ARC software suite can be configured for your use case and integrated with existing systems. We believe in flexibility, not vendor lock.
A la carte capabilities
Select only the capabilities you need for your operational workflows. ARC is modular by design, giving operators flexibility without forcing a one-size-fits-all solution.
Pair it with other tools
Integrate ARC with your existing software, workflows, and data pipelines through open APIs and flexible architecture.
Bring your own data
Leverage your proprietary observations, mission data, and third-party sources while maintaining full ownership and control.
