Question 1

What is RAG for enterprises?

Accepted Answer

RAG for enterprises is an AI architecture that retrieves relevant information from an organisation's approved knowledge sources and provides that context to an LLM before it generates an answer.

Question 2

When should an enterprise use RAG?

Accepted Answer

An enterprise should consider RAG when an AI application needs current, private, proprietary or domain-specific knowledge that is not reliably available from the model alone.

Question 3

Is RAG better than fine-tuning?

Accepted Answer

Neither is universally better. RAG is generally more appropriate when the problem is access to changing or proprietary knowledge. Fine-tuning or PEFT is more appropriate when the objective is specialised model behaviour.

Question 4

Can RAG eliminate hallucinations?

Accepted Answer

No. RAG can reduce hallucination risk by grounding answers in retrieved information, but retrieval errors, incomplete sources and model-generation errors can still occur.

Question 5

Does RAG require fine-tuning?

Accepted Answer

Usually not. A RAG system can generally connect an existing model to an external knowledge source without retraining the base model.

Question 6

Is RAG expensive?

Accepted Answer

The cost varies significantly according to data volume, retrieval infrastructure, model usage, traffic, integrations, security requirements and engineering complexity. Enterprises should evaluate cost per useful business outcome, not just infrastructure cost.

Question 7

What is the difference between RAG and an AI agent?

Accepted Answer

RAG primarily retrieves information to support generation. An AI agent can use retrieval as one component of a broader workflow in which it plans, calls tools, performs multiple steps and takes authorised actions.

Question 8

Is RAG suitable for every enterprise?

Accepted Answer

No. Some problems are better solved through prompting, conventional search, workflow automation, AI agents or model customisation. The architecture should follow the business requirement.

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