Volume 2 - Issue 2, March - April 2026

In the digital business ecosystem of today, organizations generate huge amounts of data from structured and unstructured sources through sales transactions, customer interactions, marketing campaigns, and operational processes. However, due to a lack of analytical skillsets, time constraints, and fragmented data sources, SMEs often fail to extract actionable insights from the said data. The proposed system leverages Large Language Models, LangChain orchestration, SQL-based databases, and Retrieval-Augmented Generation to provide business insights in real time without requiring technical knowledge: Natural language queries are translatedinto structured SQL queries, or document searches, the proposed solution improves decision. The three major improvements are: speed, accuracy, and accessibility. Experimental use cases in sales analysis, marketing optimization, customer segmentation, and financial forecasting demonstrate the system's effectiveness in facilitating data-driven decisions while ensuring data privacy through local model deployment.

Dr.M.Kayalvizhi, SanjeevKailash.D.G,"AI-Powered Business Analyst Using Natural Language Processing and Retrieval-Augmented Generation" International Journal of Advanced Multidisciplinary Research and Educational Development, V2(2): Page(802-806) Mar-Apr 2026. ISSN: 3107-6513. www.ijamred.com. Published by Scientific and Academic Research Publishing.