Retrieval-Augmented Generation (RAG) for Real-Time Business Intelligence

Author(s)	Gopal Rath
Country	United States
Abstract	In today's era, information is vast and overloaded which makes data-driven intelligence, real-time and context-aware information extraction a challenge. The Retrieval-Augmented Generation (RAG) mechanism can be a potential solution for dynamically retrieving information relevant to the domain. This mechanism interacts with Large Language Model (LLM) models using live data feeds, as well as BI Systems, and creates interactive, meaningful, and explainable intelligence. This paper illustrates the limitations of current BI systems, new architecture, source live data integration, and evaluation techniques with business impact. RAG for Business Intelligence can be a game changer for BI systems analytical landscape to context-based answers for complex business-driven questions
Keywords	component, formatting, style, styling, insert.
Field	Engineering
Published In	Volume 7, Issue 4, July-August 2025
Published On	2025-07-15
DOI	https://doi.org/10.36948/ijfmr.2025.v07i04.52677
Short DOI	https://doi.org/g9wnrr

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International Journal For Multidisciplinary Research