CausalCanvas

CausalCanvas is a web app (with optional desktop agent) for building, stress-testing, and communicating causal models of complex systems—without requiring a PhD. Users sketch causal loop diagrams, attach lightweight data sources (CSV, APIs), and run scenario tests that highlight feedback loops, delays, and unintended consequences. The AI assistant helps translate messy stakeholder language into structured variables, suggests missing links, and flags common modeling traps (circular definitions, double-counting, hidden delays). Outputs are board-ready: clear narratives, sensitivity charts, and “what changed and why” reports. This is not a full-blown academic simulator; it’s a practical decision-support tool for teams who need to reason about complex dynamics quickly and explain their assumptions. It targets real-world planning: policy, operations, risk, sustainability, and product ecosystems where second-order effects matter.