Natural-Language Business Intelligence

Business users often need answers that sit across many interconnected systems: finance, expenses, budgets, sales and operations. A simple question, such as which expenses were unexpectedly high this month and how they compare with budget, can require someone who knows the database structure and how to write queries. Non-technical staff end up waiting on developers or analysts.

We built an agentic AI system that takes a business question in plain English and manages the whole investigation. It works out what the question means, finds the relevant data models and how they connect, generates and checks queries, and assembles the answer. It is not a text-to-SQL wrapper: it can look beyond the obvious source, for example connecting expenses with budgets and accounting records.

The result is a conversational interface to complex enterprise data that works without knowledge of database structures or SQL. In testing on confidential client data, the agent navigated the database and returned relevant answers to real business questions. The aim is a foundation for self-service business intelligence, so specialists are not the bottleneck for every question.