In resource-constrained environments, positioning is the primary variable for survival. Brute-force planning fails against asymmetric saturation.

We utilize genetic algorithms to evolve asset placement generations against multiple threat vectors. The system weights heterogeneous points of interest (Power, C2, Logistics) to maximize systemic resilience using finite assets.

A simulation environment engineered for zero-trust architectures. Written in Rust for speed, memory safety and predictable execution patterns.

The engine leverages massive parallelization on COTS hardware, resolving tens of thousands of permutations in minutes. 100% on-premise, air-gap capable, with fully explainable 3D outputs (Explainable AI).

Threat vectors do not recognize administrative boundaries. Traditional planning creates silos that result in coverage gaps and inefficiency.

We model the defense architecture as a unified, borderless state-space. By calculating engagement envelopes across jurisdictions, the algorithm identifies coverage efficiencies that are invisible to single-state planning models.