Most teams do causal inference 4-5 times a year. Each analysis is a bespoke project: specialized talent, months of work, results scoped to one question. Everything else runs on dashboards and intuition. RootCause.ai automates the full causal pipeline on observational data. Models built in minutes (Digital Twins). No experiments required. It discovers causal structure, recovers hidden confounders, and builds a digital twin you can simulate interventions against.