REAL-TIME CAUSAL AI IN ACTION
One live decision, end to end
Follow a single anomaly on a live unit — from an unexplained deviation to a governed, explainable recommendation the operator can act on in minutes.
Detect. Rank. Explain. Simulate. Act, governed.
← Back to Real-Time Causal AITHE SCENARIO
A live anomaly on a separation unit
A continuous distillation and separation unit, running on the plant control-system layer. The column level drifts out of band. The predictive layer flagged it — but it can’t say why, or what to do.
Anonymized reference · illustrative values · full detail under NDA.
WHAT THE OPERATOR SEES
From deviation to governed action
The anomaly, explained in minutes
The causal engine attributes the live deviation to ranked factors, each with a confidence measure — not another unexplained alert to interpret.
RANKED CAUSAL FACTORS
What drives it, what counteracts it
Every node carries a signed contribution. Positive drives the anomaly; negative counteracts it — so the operator sees the corrective handle, not just a correlation.
What-if, on the same model
Before acting, test the intervention. The same validated causal model predicts the effect of a change — a counterfactual grounded in physics, not a guess.
A recommendation you can act on
The recommendation passes objectives, policy, safety, and confidence gates before it advises the operator or acts within bounds — and every step is recorded as a decision trace.
See how it’s governed →Awaiting operator confirmation · decision trace recorded
SEE IT ON YOUR PLANT
See a real deployment, on your process.
Bring a recurring anomaly you can’t explain. We’ll walk it through the causal path, end to end — ranked root cause, what-if, and a governed recommendation.
