AI-Powered Surveillance and Reconnaissance

Deploy computer vision models that autonomously detect, classify, and track objects of interest across wide-area motion imagery (WAMI) and full-motion video (FMV) feeds with >99% precision, enabling persistent surveillance without operator fatigue.

Identify anomalous patterns and suspicious activities in real-time using unsupervised learning on multi-source sensor data. Our systems reduce false alarms by 70% compared to rule-based methods, focusing analyst attention on genuine threats.

Execute inference on ruggedized edge hardware in GPS-denied environments. Our optimized SLMs and computer vision models operate with sub-2W power draw, ensuring real-time intelligence at the tactical edge without data exfiltration risk.

Fuse and correlate intelligence from GEOINT, SIGINT, and OSINT feeds into a unified operational picture. Our AI reduces data-to-decision time by 90%, enabling commanders to act on synthesized intelligence, not raw data streams.

Move from reactive monitoring to predictive intelligence. Our models analyze historical and real-time data to forecast adversary movements and likely threat events, providing a strategic window for preemptive action.

Deploy with confidence. Every model undergoes rigorous adversarial testing using the MITRE ATLAS framework to ensure resilience against data poisoning, evasion attacks, and spoofing in contested environments.