How to Prepare Your Business Documents for RAG (SME Checklist)

1. Why document preparation matters more than the AI

Many SMEs assume RAG success depends on the AI model. In reality, the quality of answers depends far more on the quality of the documents provided.

RAG does not “fix” poor documentation — it amplifies it.

This guide shows SME managers exactly how to prepare documents so AI can deliver reliable, trustworthy answers.

2. What “good RAG-ready documents” actually look like

RAG-ready documents are not:

• perfectly written,
• beautifully formatted,
• technical manuals rewritten from scratch.

They are:

• clear,
• consistent,
• up to date,
• focused on one topic at a time.

3. Step 1 — Decide what problems RAG should solve

Before touching documents, ask:

• What questions do staff repeatedly ask?
• Where do mistakes commonly happen?
• Which processes rely on one person’s memory?

Typical starting points:

• onboarding questions,
• HR policies,
• customer support procedures,
• technical instructions.

4. Step 2 — Choose a small, focused document set

Do not upload everything.

Start with:

• 5–20 key documents,
• one department or function,
• a single clear use case.

This keeps answers accurate and builds trust.

5. Step 3 — Remove outdated and duplicate content

Before feeding documents into RAG:

• delete obsolete versions,
• remove “draft” documents,
• merge duplicated guidance.

If two documents contradict each other, AI cannot know which is correct.

6. Step 4 — One document, one purpose

RAG performs best when each document focuses on a single topic.

Avoid documents that:

• mix multiple processes,
• jump between unrelated topics,
• combine policy, training and commentary.

Split them into smaller, purpose-specific files if needed.

7. Step 5 — Use clear headings and structure

Headings provide critical context for AI.

Good structure includes:

• clear section headings,
• logical progression,
• consistent naming.

Even simple headings like “Step 1”, “Step 2”, “Exceptions” make a huge difference.

8. Step 6 — Write for humans first, AI second

If a document is confusing for people, it will be confusing for AI.

Good practices:

• short sentences,
• plain language,
• explicit instructions,
• defined terms.

Avoid vague phrases like “usually”, “often” or “as required” without explanation.

9. Step 7 — Handle exceptions explicitly

Many SME processes fail because exceptions live in people’s heads.

Document:

• edge cases,
• special approvals,
• what happens when things go wrong.

This prevents AI giving overly simplistic answers.

10. Step 8 — Separate sensitive documents

Not all documents should be visible to everyone.

Before ingestion:

• identify HR-only content,
• restrict commercial contracts,
• separate disciplinary procedures.

RAG works best when access rules are applied upfront.

11. Step 9 — Use consistent terminology

Inconsistent language confuses retrieval.

Examples:

• “job” vs “project” vs “work order”
• “engineer” vs “technician”
• “client” vs “customer”

Choose one term and stick to it.

12. Step 10 — Include context, not just instructions

RAG answers improve when documents explain why, not just what.

For example:

• why a step exists,
• what risk it prevents,
• what happens if it’s skipped.

This allows AI to explain reasoning, not just steps.

13. Step 11 — Avoid tables as the only source of truth

AI can struggle with dense tables.

If key information exists only in tables:

• add short explanatory text,
• describe what the table represents,
• summarise rules in prose.

14. Step 12 — Test documents with real questions

Before rolling out:

• ask common staff questions,
• review the answers,
• identify missing or unclear guidance.

Update documents based on real usage.

15. Step 13 — Assign document ownership

Every document should have:

• a clear owner,
• a review schedule,
• a defined update process.

RAG systems stay accurate only if documents are maintained.

16. Step 14 — Keep versions simple

RAG does not need full version history.

Best practice:

• keep only the current version active,
• archive old versions outside the system.

17. Step 15 — Start small and expand

Once the first document set works well:

• add the next department,
• add more use cases,
• refine structure based on feedback.

18. The bottom line

Preparing documents for RAG is not a technical task — it’s a clarity task.

SMEs that invest a small amount of time cleaning, structuring and curating documents get:

• more accurate answers,
• higher staff trust,
• faster ROI,
• far fewer AI-related risks.

Good documents turn RAG from an experiment into a dependable business tool.