AI Powered Platform for Natural Language Database Interaction and Business Intelligence Using LLM

DOI

10.2991/978-94-6239-693-7_75How to use a DOI?

Keywords

Large Language Models (LLMs); Retrieval-Augmented Generation (RAG); Business Intelligence; Data Democratization

Abstract

Structured query language (SQL) involves technical writing expertise that poses a big obstacle to non-technical users, thereby restricting data-driven decision making at the organizational level. Available solutions like direct database clients or the conventional Business Intelligence (BI) solutions are either too complicated or lack agility. To solve this, we are introducing a web-based application that will democratize data access by providing a single platform that is integrated with AI. Our system uses Large Language Models (LLMs) through a Retrieval-Augmented Generation (RAG) pipeline to generate an executable SQL query given a natural language prompt to allow users to speak to their data. The platform combines database connectivity, schema exploration, dual mode query interface, alongside automated reporting, into a single workspace. It is secure and interoperable with Enhanced Role-Based Access Control (RBAC) and API-first structure. The testing shows that the system is indeed effective in bridging the gap between complex databases and business users and thereby making the data-driven culture a reality through providing rapid and easily accessible insights.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Pradyumna Ragothaman
AU  - B. S. Jayasri
AU  - Mohammed Adnan
PY  - 2026
DA  - 2026/06/16
TI  - AI Powered Platform for Natural Language Database Interaction and Business Intelligence Using LLM
BT  - Proceedings of the International Conference on Intelligent Systems for a Sustainable Future (ISSF 2026)
PB  - Atlantis Press
SP  - 755
EP  - 768
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6239-693-7_75
DO  - 10.2991/978-94-6239-693-7_75
ID  - Ragothaman2026
ER  -