Retail businesses generate large volumes of data, but extracting meaningful insights often requires technical expertise in SQL and data analytics. This project, Retail Insights Generator, presents an AI-powered system that converts natural language queries into SQL queries using LangChain and large language models. The system supports multilingual input, voice interaction, and intelligent recommendation features such as restock alerts and discount suggestions. It leverages a dataset of over 73,100 retail records and integrates ChromaDB for few-shot learning to improve query accuracy. The solution simplifies data access for non-technical users, enhances decision-making, and improves operational efficiency. With its lightweight architecture and user-friendly interface, the system provides an effective tool for modern retail analytics.
Sabarinath.R et al. (Tue,) studied this question.