Auria has delivered the Minimum Viable Product (MVP) of its autonomous platform, CAASI (Cognitive Autonomous Artificial System Intelligence), to the Naval Sea Systems Command (NAVSEA 03) for use in Defensive Cyber Operations. The delivery marks a significant step in efforts to advance autonomous anomaly detection capabilities for naval networks.
CAASI was developed through close collaboration with NAVSEA 03 stakeholders. The system uses patented unsupervised machine learning techniques to analyze network traffic in real time and identify suspicious behaviors, such as Advanced Persistent Threat activity, Zero-Day exploits, botnet communications, and insider threats.
Damian Dipippa, CEO at Auria, stated: “The delivery of the CAASI MVP is a major milestone not only for Auria but for the future of autonomous cyber defense in Naval and other DoD environments. We’re honored to support NAVSEA’s mission with a system built from the ground up to adapt, evolve, and operate in some of the world’s most complex and high-stakes network environments.”
CAASI operates using an unsupervised learning architecture that does not require labeled training data or predefined threat signatures. It continuously monitors live network traffic and autonomously identifies new or stealthy attack patterns. Auria’s proprietary unsupervised machine learning framework allows CAASI to adjust baselines and threat models as network behavior changes over time. The system is designed specifically for integration with Department of Defense systems and meets secure enclave operational requirements.
The delivery of CAASI aligns with NAVSEA’s broader strategy to improve cyber resilience and maintain operational continuity across naval fleets. By detecting anomalies at machine speed, CAASI aims to support human analysts by reducing dwell time, false positives, and risk exposure within mission-critical systems.
NAVSEA 03 Program Manager commented: “We are looking forward to seeing this capability in the fleet as soon as we can.”
