Model-driven risk intelligence for complex systems under extreme conditions
We develop and apply model-driven risk intelligence to help organizations understand, explore, and manage complex systems under extreme and uncertain conditions.
Risk analysis & uncertainty · Complex systems modeling · Scenario exploration · Decision support
We support understanding, anticipation, and decision-making under extreme and uncertain conditions using scientific, model-driven approaches.
SIMPLEGMA develops model-driven risk intelligence for complex systems operating under extreme, uncertain, and rapidly evolving conditions. We combine mathematical modeling, computational simulation, and data-informed analysis to support understanding, anticipation, and decision-making in high-stakes environments.
Our focus is not on dashboards or generic analytics, but on models that explain, explore, and stress-test reality—helping decision-makers reason about risk before, during, and after disruptive events.
SIMPLEGMA’s mission is to strengthen how organizations understand, simulate, and manage risk in complex systems— especially when uncertainty is high and data are incomplete. We emphasize structure over correlation, mechanisms over black boxes, and insight over automation.
We build and apply scientific models for scenario exploration (“what-if” analysis), system stress-testing, and decision support—connecting rigorous theory to actionable risk understanding.
Earthquakes, floods, cascading and compound hazards, and climate-driven extremes—supporting scenario exploration, impact pathways, and risk-informed planning.
Infrastructure resilience, structural performance, systemic vulnerabilities, and interdependencies across urban systems— from component behavior to city-scale risk emergence.
Population dynamics, epidemiology, and ecosystem stress—using mechanistic and agent-based approaches to explore spread, persistence, and intervention strategies under uncertainty.
Computational acoustics and wave-mechanics-informed approaches for noise management and sound environment optimization in structures and urban settings. (PDF)
Cross-domain modeling of interacting components, feedbacks, and nonlinear dynamics—supporting robust reasoning when systems operate outside “normal” regimes.
SIMPLEGMA follows a model-centric philosophy: we clarify system structure, translate it into mathematical/computational form, explore scenarios systematically, and translate model behavior into decision-relevant insight.
Data are used where available — but models lead the reasoning.
We’d love to hear from you. If you face a problem where uncertainty matters, structure matters, and risk cannot be simplified, we should talk.
Email: info@simplegma.com