Retrieval-Augmented Generation in Enterprise Knowledge Systems

Authors

  • Bhaskar Babu Narasimhaiah Author

Keywords:

Keywords: Retrieval-Augmented Generation, Enterprise Knowledge Management, Vector Database, Large Language Models, Document Chunking, Performance Benchmarking, AI System Architecture, GraphRAG, Deployment Optimization, Multimodal Retrieval

Abstract

Retrieval-Augmented Generation (RAG) has fundamentally transformed  enterprise knowledge management by enabling dynamic, context-aware  responses grounded in up-to-date, proprietary data. By September 2024,  the global RAG market reached $1.2 billion, with enterprise adoption  accelerating to over fifty percent, outpacing the $13.8 billion spent on AI  initiatives that year.

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Published

21-10-2024

Issue

Vol. 2 No. 2 (2024): July-December 2024

Section

Articles

How to Cite

Retrieval-Augmented Generation in Enterprise Knowledge Systems. (2024). AI Tech International Journal, ISSN: 3079-4749, 2(2), 47-58. https://techaijournal.com/index.php/AIjournal/article/view/22