Automatically transform raw data into sophisticated Causal AI models that deliver not only superior predictions but are also intrinsically explainable & augment the decision making process, factoring real-world constraints
While today’s ML models just track patterns in data, Causal AI models represent how systems really work and are intrinsically explainable. Causal AI models allow users to evaluate the impact of actions ahead of time and answer “why”-questions, going far beyond standard predictive analytics. causaLab makes Causal AI models accessible to everyone.
Conventional ML just identifies correlations — but correlation is not causation
From a causal graph to a predictive model
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