Kausalyze is a University of Sheffield spinout founded by chemical engineers, developing causal AI for process manufacturing. Its platform helps manufacturers understand why recurring plant problems occur, rather than simply detecting anomalies or predicting failures. Using a causal model of connected process variables, it traces issues to upstream drivers and presents evidence that engineers can inspect and validate.

The platform supports process-health monitoring, root-cause diagnosis, forecasting time to operating limits, and testing proposed interventions. Teams can compare set-point changes with leaving conditions unchanged, review predicted downstream effects, and assess expected impacts on production, energy use, or maintenance before deciding what to implement through existing procedures. Kausalyze positions its technology as a physics-informed, engineer-validated alternative to tools that identify symptoms without explaining their causes.

The company proposes starting with a 12- to 16-week pilot on one unit, using the site’s own records to establish value. Kausalyze is backed by Innovate UK, Plug and Play Tech Center, and Greentown Labs.