Agentic AI System - Natural language data exploration with autonomous agents

Business teams often struggled to get timely answers from data. Even simple questions like “What was churn in EMEA last quarter?” required waiting for analysts to write SQL, run the query, and explain the results. This created constant delays, made decision-making slower, and left analysts spending too much time on repetitive requests instead of strategic work.

To solve this, I built a conversational AI assistant that acts like a virtual analyst. Users ask questions in plain English. Behind the scenes, a system of specialised agents handles each step: interpreting the question, identifying the relevant tables and fields, generating and validating a SQL query, running it in BigQuery, and turning the results into a clear, business friendly explanation. A central manager agent oversees the workflow and ensures quality at every stage.

The assistant is connected to the company’s internal knowledge base, allowing it to use accurate definitions and add helpful context to its answers. It integrates into existing systems, respects data governance rules, and provides reliable insights in under a minute. This shifted how teams use data day to day, they no longer rely on manual reports and instead get fast, trusted answers whenever they need them.