Why Causal AI?
Move beyond correlation. Understand cause and effect. Make decisions based on evidence, not assumptions.
The Limits of Traditional AI
Correlation is not causation. Traditional ML can't tell you if ads caused purchases, or if high-intent customers simply see more ads.
Forecasts outcomes based on historical patterns
Produces content from learned patterns
Identifies true cause-and-effect relationships
Leading European Expertise
Economic AI™ brings together leading European experts in causal inference, econometrics, and machine learning. Our team has published foundational research in top journals including the American Economic Review, The Econometrics Journal, and the Journal of the Royal Statistical Society.
Causal AI Across Industries
Actionable insights that correlation-based approaches miss.
Finance & Banking
- Measure true impact of marketing on deposit growth
- Identify drivers of credit application conversion
- Understand customer retention causally
Insurance
- Determine what drives policy conversion
- Separate correlation from causation in renewals
- Optimize pricing with causal understanding
Manufacturing
- Identify root causes of quality issues
- Optimize rework policies with causal evidence
- Measure true ROI of process improvements
The Causal Advantage
Enterprise-grade causal inference delivers measurable business impact.
Better Signal-to-Noise
Separate true effects from spurious correlations
Valid inference after model selectionClear Revenue Attribution
Know which actions actually drive results
Measuring heterogeneous treatment effectsFaster Decisions
Identify ineffective activities before wasting budget
Sensitivity analysis for Causal MLReady to move from correlation to causation?
Our team combines cutting-edge research with practical implementation.
“Mastery is the transition from predicting what happens to understanding why it must.”
Trusted by Industry Leaders
