A confident, fluent, and factually wrong answer from a language model. The model is predicting plausible text, so a fabricated price, clause, or citation looks exactly like a correct one.
This is the central risk of putting AI in front of customers: a wrong answer about a refund policy or a dosage is not a bug report, it is a liability. The problem cannot be fully eliminated, only contained.
We ground answers in your documents with citations, constrain the model to a defined scope, validate structured output against schemas, and route low-confidence cases to a human instead of guessing.