Business users query enterprise data in plain language

Business users kept hitting the same wall. Getting answers out of complex structured data meant waiting for someone technical to write the SQL. We set out to remove that dependency.

What we built

We built an agentic business intelligence platform that lets people query enterprise datasets in plain language instead of SQL. Underneath, a multi-agent workflow built on LangGraph coordinates specialized agents for schema retrieval, SQL generation, validation, query execution, and response generation.

To keep answers accurate and grounded in the real data, the platform uses metadata-driven context and retrieval-augmented generation. SQL validation and guardrails catch invalid queries before they run, so responses stay reliable.

We designed it as a reusable accelerator that plugs into enterprise databases across different business domains.

The outcome

People now get analytical answers by asking a question in their own words, which cuts the time it takes to answer a data question. Teams lean far less on technical staff, because non-technical users can work with structured data directly. And because it is an extensible, open-source accelerator, it adapts to a wide range of enterprise data environments and analytics use cases.