Auria has announced the delivery of its Minimum Viable Product (MVP) for CAASI, an autonomous platform designed to support defensive cyber operations, to the Naval Sea Systems Command (NAVSEA 03). The system is intended to advance anomaly detection capabilities within naval networks.
CAASI, developed with input from NAVSEA 03 stakeholders, operates as an unsupervised machine learning system. It analyzes network traffic in real time and is capable of identifying various forms of anomalous or malicious activity, such as advanced persistent threats, 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 features an unsupervised learning architecture that does not require labeled training data or predefined threat signatures. It monitors live network traffic continuously and autonomously detects new or stealthy attack patterns. The system uses Auria’s proprietary patented unsupervised machine learning framework to adjust baselines and threat models as network behavior changes. CAASI is optimized for integration into Department of Defense systems and meets secure enclave operational requirements.
The delivery supports NAVSEA’s strategic initiative to improve cyber resilience and operational continuity across naval fleets. By providing real-time anomaly detection at machine speed, CAASI aims to assist human analysts by reducing dwell time on threats, lowering false positives, and decreasing risk exposure in mission-critical systems.
NAVSEA 03 Program Manager commented: “We are looking forward to seeing this capability in the fleet as soon as we can.”
