Built by Operators, for Operators.

Dr. Lisa Dolev and her team at Qylur Intelligent Systems set out to reinvent how people and places are protected. They built an entry security system that fused scanning sensors, AI, and automation into a single threat detection solution. It worked. The system was deployed at Disneyland, the FIFA World Cup, the Super Bowl and Levi's Stadium.

But success surfaced a deeper problem: deployed AI doesn't stay sharp on its own. As conditions, threats, and sensors shifted from venue to venue, models that performed flawlessly at one site began to degrade at the next. In addition, as specialized model variants were deployed, maintaining the performance of the exponential permutations became unmanageable and cost prohibitive.

The team set out to solve it, and the answer became SNIM^® AI, the Social Network of Intelligent Machines: a way for connected machines to share what they learn, monitor each other's performance, and adapt in the field. What began as a failsafe for physical security became a broader platform for keeping intelligent systems intelligent everywhere they're deployed.

The U.S. Air Force awarded multiple SBIR contracts to explore how SNIM^® AI could speed up fielding of AI-based drones, UAVs, and ground systems, and to transform the platform for use by networks of intelligent autonomous systems within the DoD. The interest centered on keeping networks of autonomous systems in contested environments reliable over time, using SNIM^® AI as the performance-monitoring layer for edge devices and autonomous fleets.

SNIM^® AI is the operational intelligence layer required for managing millions of autonomous machines to ensure they perform as expected in real-world conditions.

By making deployment viable we're unlocking a future where autonomous systems uplift humanity.