If 2024 was the year companies tested ChatGPT/LLMs, 2025 is the year to operationalize AI—embed it into workflows, tie it to internal data, and measure impact against real KPIs. But there’s a hard truth: LLMs can sound confident and still be wrong. In business contexts, a single inaccurate answer about pricing, policies, compliance, or procedures can create customer issues, operational mistakes, and even legal risk.
That’s why RAG (Retrieval-Augmented Generation) has become one of the most practical architectures for enterprise AI: it combines the power of LLMs with verified internal knowledge (SOPs, policies, contracts, product docs, training materials, FAQs, and more).
In this article, NKKTech Global—an AI company focused on enterprise implementation—shares why Vietnamese businesses should adopt RAG starting in 2025 to reduce risk, unlock data value, and build sustainable competitive advantage.
What is RAG—and why it matters for enterprise AI?
RAG is an approach that combines:
- Retrieval: finding the most relevant information from your internal knowledge base (PDF/Word/Excel, wiki, CRM/ERP, FAQs, manuals, onboarding docs, etc.)
- Generation: using an LLM to produce an answer grounded in those retrieved sources
Instead of “ask an LLM and hope it’s correct,” RAG helps the assistant answer based on your actual documents—which is exactly what enterprises need.
7 reasons Vietnamese businesses should adopt RAG in 2025
1) Reduce hallucinations and protect operational reliability
LLMs can hallucinate—respond fluently but incorrectly. For businesses, wrong answers about pricing, product specs, policies, contracts, and procedures can lead to:
- customer complaints
- inconsistent internal handling
- compliance and legal exposure
RAG significantly improves trustworthiness by grounding responses in real sources.
2) Turn existing internal documents into a searchable knowledge asset
Many Vietnamese businesses already have valuable knowledge—but it’s scattered:
- SOPs in Word/PDF
- pricing and product catalogs in Excel
- training and onboarding materials
- email threads and meeting notes
- ERP/CRM/HRM data exports
RAG transforms this into an ask-and-answer internal knowledge system, reducing reliance on “asking the one person who knows.”
3) Clear ROI: faster search, faster decisions, fewer repetitive support requests
RAG delivers fast value in common pain points:
- Customer Support: reduce repetitive tickets, speed up responses
- Sales/Presales: quickly retrieve product/policy/case-study info
- Internal Ops: HR/IT helpdesk deflection and faster resolution
- Operations: standardized answers aligned to official policy
The advantage: you can launch without months of model training and still measure impact early.
4) Built for fast-changing environments (a common Vietnam reality)
Policies and procedures change frequently. Re-training or fine-tuning for every update is slow and costly. With RAG:
- update the documents → the assistant updates automatically
- no need to re-train the whole model for each change
5) Stronger security and access control (when implemented correctly)
Data leakage is a top concern. With enterprise-grade RAG, you can implement:
- role-based access (by department, function, seniority)
- restricted retrieval scopes (only approved sources)
- audit logs for compliance
- deployment options (private cloud / on-prem) depending on requirements
As an AI company, NKKTech Global treats security, governance, and compliance as core design requirements—not add-ons.
6) A foundation for AI Agents and workflow automation
The 2025–2026 shift is from “chatbots that answer” to agents that act:
- creating tickets, reports, summaries
- filling forms, preparing documents
- executing multi-step workflows
To act correctly, an agent needs a “single source of truth.” RAG is the knowledge layer that ensures agents retrieve accurate information before taking action.
7) Competitive advantage while most of the market is still experimenting
Many companies remain stuck at demo stage. Businesses that deploy RAG early gain:
- faster decision-making
- higher service quality
- leaner operations
- teams that build “AI muscle” through real workflows
This advantage compounds over time.
How to start RAG in a way that actually works
Step 1: Choose 1–2 use cases with clear data and measurable KPIs
Great quick wins:
- Customer policy FAQ (returns, warranty, pricing rules)
- Internal SOP assistant (HR/IT/Finance)
- Product and technical documentation assistant
- Email/document drafting grounded in templates + policy
Step 2: Make your data “good enough”—not perfect
Start by:
- organizing docs by topic
- setting naming/version rules
- removing outdated documents
- defining “source-of-truth” documents
Step 3: Design the RAG architecture properly (not just “vectorize everything”)
High-performing RAG often requires:
- strong chunking strategy (sections, clauses, tables)
- hybrid search (semantic + keyword)
- reranking for accuracy
- prompting & citation strategy (answers with references)
Step 4: Evaluate with real questions from real workflows
Build a test set using actual tickets/emails and measure:
- answer accuracy
- groundedness (is it supported by sources?)
- time-to-answer
- deflection rate (reduced human workload)
Step 5: Implement security and permissions from day one
- role-based access by department
- project/client-based data separation
- logs + monitoring for sensitive queries
Common RAG use cases in Vietnam (by industry)
Retail / Commerce: policy assistant (returns, promotions), product guidance
- Finance / Banking: internal procedures, forms, compliance knowledge
- Manufacturing: SOPs, QC checklists, troubleshooting guides
- Real Estate: project info, legal docs, contract templates, sales policy
- Tech / Outsourcing: project knowledge base, onboarding, delivery playbooks
How NKKTech Global helps Vietnamese businesses implement RAG
NKKTech Global is an AI company delivering enterprise-ready AI solutions that are measurable, secure, and scalable. Our typical RAG approach includes:
- Discovery (use cases, KPIs, data sources)
- Architecture & security design
- Rapid POC (often 2–4 weeks depending on scope)
- Iterative rollout (sprint-based optimization)
- System integration (ERP/CRM/HRM/Line/Chat)
- Monitoring, evaluation, and cost optimization
If you want to turn internal documents into operational advantage in 2025–2026, RAG is one of the safest and most effective starting points.
Contact Information:
🌐 Website: https://nkk.com.vn
📧 Email: contact@nkk.com.vn
💼 LinkedIn: https://www.linkedin.com/company/nkktech
