Supersimple lets people ask questions across a data warehouse in plain language, but the interesting part is what constrains the answers. Natural-language BI has been attempted many times and usually fails on trust: the tool produces a number, nobody can tell how it was derived, and the analytics team ends up re-checking everything, which is the work it was supposed to remove.
Two features address that directly. Answers are built on governed definitions, so revenue means the one agreed definition rather than whatever the model inferred from column names. And search is permission-aware, so results respect the access rules already in place instead of quietly exposing data a user should not see. Explainability closes the loop by showing how an answer was constructed.
It also spans company knowledge alongside warehouse data, which matters because real business questions rarely resolve inside the warehouse alone. This is a platform for organisations with an existing warehouse and defined metrics, not a substitute for building them.
