Industrial Intelligence Solutions with Causal AI : Daniele Gamba - CEO, AISent Srl
For decades, manufacturers have relied on traditional analytics—correlations, trendlines, dashboards—to make operational decisions. But there's a limit:
Correlation ≠ Causation
Just because two variables move together doesn’t mean one causes the other.
This blind spot can lead to poor decisions and surface-level fixes that don’t solve the real issue.
For example, a machine’s temperature spikes often coincide with defects. Traditional analytics might alert you when it happens—but not why. Is it the temperature? A faulty sensor? Operator error?
Causal Inference flips the script. Instead of just…
The skinny
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