Natural Language to SQL Queries Using LLM Models

The increasing reliance on data-driven decision making has made database interaction a critical component in many domains. However, writing Structured Query Language (SQL) queries requires specific technical knowledge, which creates an accessibility barrier for non-technical users. This project proposes a Natural Language to SQL (NL2SQL) system that utilizes Large Language Models (LLMs) to convert user queries expressed in everyday language into valid SQL statements. The system enables users to retrieve information from a database without requiring prior SQL expertise, improving usability and broadening access to data insights.

• Publication year

  2025

• Venue

  2025 2nd International Conference on Artificial Intelligence and Knowledge Discovery in Concurrent Engineering (ICECONF)

• Publication date

  2025-10-09

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1109/ICECONF65644.2025.11379599
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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