Industrial AI in Chemicals: From Data Foundation to Operational Scale
Most Industrial AI initiatives in chemicals don't stall because of the models. They stall because the data beneath them can't be trusted, queried, or acted on at scale. This ebook documents how Celanese, NOVA Chemicals, and Koch Ag & Energy Solutions built the right foundation first - and the results that followed.
The returns are independently verified. Forrester TEI™ research finds that Cognite customers across asset-intensive industries achieve 465% ROI, $29.4M net present value, and payback in under six months.
How Celanese built a unified manufacturing portal scaling across global facilities - now running NVIDIA forecasting models on the same foundation
How NOVA Chemicals cut data discovery time by 30% across 11 sites and nearly doubled NPV by compressing their transformation timeline by three years
How Koch Ag & Energy Solutions onboarded 6 sites in under 6 months, with a 7th completed by their internal team in under two months
The architecture decision that determines whether Industrial AI scales or stalls - including a platform vs. DIY cost breakdown
