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eISSN: 2581-9615 || CODEN (USA): WJARAI || Impact Factor: 8.2 || ISSN Approved Journal

A Multi-Layer Intelligent Agent Framework for Real-Time Business Data Analytics and Optimization

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  • A Multi-Layer Intelligent Agent Framework for Real-Time Business Data Analytics and Optimization

Emmanuel C. Chukwu 1, *, Emmanuel N. Ekwonwune 1, Comfort C. Olebara 1 and Prisca I. Okochi 2

1 Department of Computer Science, Imo State University, Nigeria.

2 Department of Computer Science, Michael Okpara University of Agriculture Umudike, Abia State Nigeria.

Research Article

World Journal of Advanced Research and Reviews, 2025, 28(02), 2280-2284

Article DOI: 10.30574/wjarr.2025.28.2.3959

DOI url: https://doi.org/10.30574/wjarr.2025.28.2.3959

Received on 17 October 2025; revised on 22 November 2025; accepted on 25 November 2025

Businesses today handle more data than ever before, yet many still struggle to turn that data into clear, timely, and meaningful decisions. Traditional analytics tools often work in silos, require a lot of manual work, and respond too slowly to the fast-paced nature of modern markets. To address this gap, this research proposes a multi-layer intelligent agent framework designed to automate data gathering, streamline data processing, and deliver real-time analytics for better business optimization. The framework is built around several coordinated layers—data acquisition, preprocessing, machine learning analytics, and decision support—working together like an intelligent ecosystem. The study demonstrates how this layered AI agent structure can significantly improve decision-making, reduce operational delays, and help businesses respond more quickly to changing conditions.

AI Agent; Business Data Optimization; Machine Learning (ML); Data Mining

https://journalwjarr.com/sites/default/files/fulltext_pdf/WJARR-2025-3959.pdf

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Emmanuel C. Chukwu, Emmanuel N. Ekwonwune, Comfort C. Olebara and Prisca I. Okochi. A Multi-Layer Intelligent Agent Framework for Real-Time Business Data Analytics and Optimization. World Journal of Advanced Research and Reviews, 2025, 28(02), 2280-2284. Article DOI: https://doi.org/10.30574/wjarr.2025.28.2.3959.

Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0

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