Developing causal AI tools to formulate and analyze the impacts of policies within complex systems.
Watch how policy levers reposition outcomes as new simulations surface in real time.
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Experience our cutting-edge causal AI system that helps policymakers understand complex scenarios, visualize causal relationships, and simulate policy interventions before implementation.
Interactive visualizations of causal relationships between policy variables
Natural language conversations about policy scenarios and interventions
Model policy interventions and explore potential outcomes and consequences
Our core thesis is that policy, like science and engineering, must be exploratory in nature—capable of simulating, testing, and adapting to uncertain technological frontiers.
Policy systems lack the tools and protocols to anticipate, test, and iteratively improve responses to high-uncertainty, fast-moving technological change.
This leads to reactive governance, misaligned incentives, and increased systemic fragility.
By integrating agent-based modeling, causal inference, and large language models, we provide policymakers with interactive platforms to:
Exploring how causal models can improve policy effectiveness by identifying true cause-and-effect relationships.
Using computational simulations to test complex systems policies before implementation in the real world.
Why policymakers need to adopt experimental approaches to navigate technological uncertainty.
Visualize and modify causal relationships between key variables to understand how changes in one factor affect others throughout the system.
Monitor real-time system responses to policy changes as they cascade through stakeholders, markets, regulations, and social systems.
Interact with our AI assistant to ask questions about policy impacts, explore alternative scenarios, and receive insights on potential outcomes.
CEO
Chief Technical Officer
Economic Officer
Intergrated Deployment Policy
Professor at Stanford University
Advisor, Strategic Deterrence