About CausoAI
We make causal inference accessible.
Every analytics team deserves to know the true causes of their business outcomes — not just what correlated with what. We built CausoAI to make that possible, without requiring a team of causal inference researchers.
Our Mission
Close the gap between data and decision.
Most business decisions are still made on correlation-based analytics. Teams know what happened and can predict what will happen — but they can't reliably answer why, or know which interventions will actually work.
Causal inference has existed in academia for decades. The tools exist — DoWhy, EconML, CausalLearn — but applying them correctly requires deep expertise. CausoAI wraps those tools in a production-ready platform that enforces rigor automatically, so any analytics team can access causal-quality insights.
Our Principles
Causation over correlation
Correlations mislead. Causal models make better decisions. We build tools that enforce this distinction.
Automated, not manual
Causal analysis shouldn't require a PhD. Our platform handles algorithm selection, assumption checking, and interpretation.
Explainable to executives
Statistical outputs only matter if decision-makers understand them. AI-generated plain-English summaries bridge that gap.
Rigorous by default
The CRS validation layer makes it hard to run a bad analysis — and tells you exactly what to fix when something is wrong.