Natural Language Query Engine for Relational Databases using Generative AI

TL;DR

This paper presents a natural language query engine that uses Generative AI to translate user questions into SQL and generate understandable responses, making database access more accessible for non-technical users.

Contribution

It introduces a novel AI-driven system that automatically converts natural language queries into SQL and provides natural language answers, reducing the need for SQL expertise.

Findings

Accurately translates natural language to SQL with high syntactic and semantic correctness.

Generates clear, natural language responses from database data.

Democratizes data access for non-technical users.

Abstract

The growing reliance on data-driven decision-making highlights the need for more intuitive ways to access and analyze information stored in relational databases. However, the requirement of SQL knowledge has long been a significant barrier for non-technical users. This article introduces an innovative solution that leverages Generative AI to bridge this gap, enabling users to query databases using natural language. Our approach automatically translates natural language queries into SQL, ensuring both syntactic and semantic correctness, while also generating clear, natural language responses from the retrieved data. By streamlining the interaction between users and databases, this method empowers individuals without technical expertise to engage with data directly and efficiently, democratizing access to valuable insights and enhancing productivity.