Space & Satellite Networks
The Challenge: Current space traffic management systems are reactive and based on limited, deterministic models of orbital mechanics.
Our Rulial Lens: We model orbital space as a branchial graph where each node represents a possible future configuration of assets and debris.
The Outcome: Proactive collision avoidance and constellation optimization that accounts for all possible future scenarios.
Finance: Branchial Risk Modeling
The Challenge: Traditional models struggle with “black swan” events and systemic risks in interconnected financial systems.
Our Rulial Lens: We model the market as a branchial graph of possible economic futures rather than a single predicted path.
The Outcome: Robust portfolios, optimized trading strategies, and early systemic risk detection.
Defense & Cybersecurity
The Challenge: Current C2 systems are reactive and based on predetermined courses of action that fail against adaptive threats.
Our Rulial Lens: We frame the battlespace as a rulial multi-graph of possible threat and response pathways.
The Outcome: Pre-emptive threat forecasting, multi-domain command advantage, and resilient communications.
Logistics & Marine
The Challenge: Logistics software is shattered by disruptions and cannot model complex, interacting variables at global scale.
Our Rulial Lens: We model global networks as a physical branchial graph where routes represent possible paths through space-time.
The Outcome: “Supply chain immunity” and robust route optimization against all possible disruption futures.