Secure Natural-Language Analytics for Business Data

Business teams expect direct access to operational data, yet many ad hoc questions still wait on analysts to translate business intent into database logic. Generative AI can remove that bottleneck, but giving a model direct access to enterprise data raises real concerns about privacy, governance, reliability, and accountability.

In this white paper, we evaluate a governed approach: an external language model interprets the question and proposes a query, while data access, policy enforcement, execution, and results stay inside a trusted environment. Across 12 business questions, two database environments, and 44 model configurations, we found that more reasoning didn’t reliably improve answers, that repeated schema context drove most processing cost, and that business meaning can’t always be inferred from schema alone.