Longer methodological work (identification, estimation, validation) for a technical audience.
White papers (the method in depth, in a standalone document) are in progress. Request access to be notified when the first one publishes.
Independent coverage that places causal AI (and Parabole) in the industrial-AI landscape.
BofA Global Research’s write-up of its Industrial AI Conference in New York, where Fortive, Rockwell, Boston Consulting Group and Parabole presented. It covers how manufacturers are monetizing AI (inside their own plants and as a product) and reports on Parabole’s customer panel: a causal model that saved up to 10% on raw materials in a key value stream and moved roughly 90% of orders to touchless, with the line that stuck: “if you want the 99.999% confidence, you need causal.” This was a panel statement, not a reported statistical confidence level.
Gartner’s annual map of where each AI technique sits between the Innovation Trigger and the Plateau of Productivity. Causal AI is rated a high-benefit innovation two-to-five years from mainstream adoption (valued for robustness in changing conditions, data efficiency and explainability) and Parabole.ai is named among the sample vendors. The report also profiles the adjacent techniques a TRAIN deployment draws on: first-principles AI, composite AI, decision intelligence and knowledge graphs.
Both reports are the copyright of their publishers. The full reports are not redistributed here; the summaries above reflect their published findings.
Bring the engineer who knows the process. We will walk through the causal model behind it.