research article
Retrieval-Augmented Generation in Enterprise Knowledge Systems
Vol. 2 , Issue 2 (2024) · pp. 47-58
DOI: https://doi.org/10.64180/oct.techai.240207
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.
Keywords:
Retrieval-Augmented Generation
Enterprise Knowledge Management
Vector Database
Large Language Models
Document Chunking
Performance Benchmarking
AI System Architecture
GraphRAG
Deployment Optimization
Multimodal Retrieval
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