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Implementation Published on 2026-09-15 · 10 min read

Enterprise AI Implementation: Private RAG vs. Model Fine-Tuning Architectural Blueprint

A practical evaluation matrix covering factual latency, operational costs, hallucination boundaries, and Hong Kong InfoSec compliance for CIOs.

For high-stakes enterprise workflows—such as financial audits, legal synthesis, and public administration—selecting between RAG and Fine-Tuning dictates capital ROI and security posture.

1. Knowledge Freshness: When ordinances, compliance standards, and manuals update continuously, RAG provides deterministic second-level sync without costly GPU re-training.

2. Hallucination Control: Critical decisions demand strict citation lineage. RAG models ground citations directly in authoritative corporate records.

3. Hybrid Production Blueprint: We advocate open-weight foundation models integrated with GraphRAG pipelines and lightweight LoRA adaptations, delivered alongside comprehensive Hong Kong PDPO / SRAA / ISO 27001 compliance audit documentation.

Keywords: #RAG Architecture#Fine-Tuning#Private AI#InfoSec Compliance Audit
Practice: Evergrav Senior Advisory Practice
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