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Implementation of Retrieval Augmented Generation for Intelligent Cloud Enterprise Knowledge Discovery and Decision Support

Cian O Maidin

Team Lead, NearForm, Waterford, Ireland

Abstract

The exponentiation of unstructured enterprise data, distributed across multi-cloud silos and legacy document repositories, presents a critical challenge for corporate knowledge management and real-time decision support. Standard large language models (LLMs) natively exhibit severe constraints when deployed within specialized corporate environments, primarily due to explicit knowledge cutoffs, structural hallucination propagation, and a total absence of intra-organizational data permission awareness. This paper presents a next-generation framework for the implementation of Retrieval-Augmented Generation (RAG) engineered specifically for intelligent cloud enterprise knowledge discovery. By synthesizing a multi-stage retrieval architecture—incorporating parallelized sparse-dense hybrid search indices, dynamic semantic parsing, and machine-learning-driven cross-encoder reranking—the framework provides a robust cognitive architecture for processing heterogeneous data formats. Crucially, the system introduces a deterministic security layer featuring document-level role-based access control (RBAC) and dynamic data masking mapped natively into the vector collection payloads. Empirical performance profiling across scaled cloud-native vector architectures demonstrates significant advancements in retrieval precision, context optimization efficiency, and answer grounding. Ultimately, this research provides an operational blueprint for deploying secure, deterministic, and highly accurate decision support systems capable of accelerating strategic corporate workflows without exposing sensitive proprietary data assets.

Article Information

Journal

International Journal of Emerging Trends in Engineering and Management Research

Volume (Issue)

Vol. 10 No. 6 (2025): International Journal of Emerging Trends in Engineering and Management Research (IJETEMR)

DOI

https://doi.org/10.15662/ijetemr.2025.1006005

Pages

18925-18932

Published

December 10, 2025
Copyright

Open Access

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

How to Cite

Cian O Maidin (%2025). Implementation of Retrieval Augmented Generation for Intelligent Cloud Enterprise Knowledge Discovery and Decision Support. International Journal of Emerging Trends in Engineering and Management Research , Vol. 10 No. 6 (2025): International Journal of Emerging Trends in Engineering and Management Research (IJETEMR) , pp. 18925-18932. https://doi.org/10.15662/ijetemr.2025.1006005

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