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Articles

Scalable Enterprise Cloud Integration Using Retrieval-Augmented Generation and Governed Data Architectures with Access Control

Dr. Ismail Shahin

Professor, University of Sharjah, United Arab Emirates

Abstract

Enterprise cloud integration has become increasingly complex as organizations manage distributed applications, heterogeneous data sources, and growing demands for secure, intelligent information retrieval. Retrieval-Augmented Generation (RAG) offers a promising approach by combining large language models with enterprise knowledge repositories to generate contextually relevant and evidence-based responses. However, implementing RAG within large-scale cloud environments requires robust integration mechanisms, governed data architectures, and comprehensive access control policies. This study examines a scalable enterprise cloud integration framework that incorporates RAG, centralized governance, distributed data processing, and identity-aware authorization. The proposed approach integrates structured and unstructured data from enterprise resource planning systems, customer relationship management platforms, document repositories, and cloud-native applications through standardized application programming interfaces and event-driven pipelines. Data governance mechanisms support data quality, lineage, classification, retention, and regulatory compliance, while role-based and attribute-based access control restrict information retrieval according to user permissions and organizational policies. The methodology adopts a design-oriented research approach involving architectural modeling, prototype development, and evaluation against scalability, retrieval accuracy, response latency, security, and operational efficiency. The framework also considers tenant isolation, encryption, auditability, vector database management, and continuous monitoring to improve reliability in dynamic enterprise environments. The study establishes a conceptual foundation for integrating generative artificial intelligence into governed cloud ecosystems without compromising confidentiality or administrative accountability. The proposed architecture provides practical guidance for organizations seeking secure, scalable, and maintainable AI-enabled enterprise information systems

Article Information

Journal

International Journal of Advanced Engineering Science and Information Technology (IJAESIT)

Volume (Issue)

Vol. 8 No. 6 (2025): International Journal of Advanced Engineering Science and Information Technology (IJAESIT)

DOI

https://doi.org/10.15662/IJAESIT.2025.0806021

Pages

17900-17907

Published

November 19, 2025
Copyright

Open Access

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Dr. Ismail Shahin (2025). Scalable Enterprise Cloud Integration Using Retrieval-Augmented Generation and Governed Data Architectures with Access Control. International Journal of Advanced Engineering Science and Information Technology (IJAESIT) , Vol. 8 No. 6 (2025): International Journal of Advanced Engineering Science and Information Technology (IJAESIT) , pp. 17900-17907. https://doi.org/10.15662/IJAESIT.2025.0806021

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