Data quality has long been recognized as a cornerstone of reliable decision-making and trustworthy outputs, particularly in the age of AI. Many organizations have invested significant effort in improving the quality of their data, such as preparing source texts for chatbot interactions. In highly regulated sectors like health insurance, this challenge is amplified by the volume of legal and operational regulations and constant changes, like those affecting reimbursement rules.