Practical guide
Preparing documents for RAG and AI knowledge bases
Preparing files for RAG starts before indexing: convert documents into Markdown with stable headings, source metadata, clean tables, removed boilerplate, and access-control boundaries. Each section should still make sense when retrieved alone. Review sensitive data, dates, owners, versions, links, and table structure before putting converted Markdown into a vector database or AI knowledge base.
Last reviewed July 17, 2026 · Release 2026-07-17-adsense-r9
Who this guide is for
- • Documentation and content teams
- • Developers building retrieval pipelines
- • Researchers organizing source collections
- • Teams migrating approved documents into AI knowledge bases
What makes Markdown useful for RAG?
Markdown exposes headings, lists, links, code, and regular tables as visible text structure. These boundaries can guide chunking and make retrieved passages easier to cite. Markdown does not automatically solve source quality, access control, metadata, duplication, or table interpretation.
What source metadata should every converted file keep?
Keep a stable source title, original filename or system ID, canonical source URL when available, owner, publication or effective date, version, last reviewed date, access classification, and conversion notes. Put this metadata in front matter or a consistent header rather than repeating it inside every chunk.
What boilerplate should be removed before indexing?
Remove repeated headers, footers, navigation, cookie text, page numbers, legal boilerplate that is unrelated to the answer task, duplicated tables of contents, and repeated slide agendas. Keep disclaimers or definitions that materially change interpretation.
How should tables be prepared for retrieval?
Use regular Markdown tables for small grids. For wide or complex tables, split by topic, add a prose summary, or turn each record into a short section. Keep units and header context inside any chunk that may be retrieved alone.
How should private documents be handled?
Apply access controls before conversion and indexing. Do not use a public upload for confidential, regulated, customer, financial, medical, legal, credential-containing, or private source material unless the workflow is approved. Redaction does not replace authorization.
What should a review log contain?
Record the source, conversion date, converter release, reviewer, known warnings, sensitive-data decision, table checks, removed boilerplate, and the final approval state. A review log helps explain why a knowledge-base answer may differ from the original document.
Before and after example
Before
Page 4 INTERNAL Product policy Owner: Operations Version 3 [repeated footer] A wide 18-column table...
After Markdown
--- title: Product policy owner: Operations version: 3 access: internal-approved source_page: 4 --- ## Policy scope ... ## Key table summary The policy has three approval states...
Review checklist
- • Every chunk has enough source context to be understood alone.
- • Dates, owners, versions, units, and links are present and verified.
- • Repeated boilerplate and duplicate content are removed.
- • Tables are split or summarized without losing header meaning.
- • Sensitive content and permissions are reviewed before indexing.
- • The original source and a conversion review log remain available.
Risk boundary
Converted Markdown remains a draft. Use an approved private workflow for confidential, regulated, customer, financial, medical, legal, credential-containing, or private source material. Keep the original source available until all material details are verified.
Frequently asked questions
Should one large document be split before indexing?
Usually yes when sections answer different questions. Split at stable headings and keep source metadata with every chunk.
What metadata should be included in Markdown?
At minimum: title, source ID or URL, owner, date, version, access classification, and last reviewed date.
Should headers and footers be removed?
Remove repeated page furniture unless it changes legal meaning, scope, or attribution.
How should tables be chunked?
Keep small regular tables together. Split wide tables by topic or convert each record into a self-contained section.
Can I index sensitive files after conversion?
Only under an approved private workflow with authorization and access controls. Conversion does not make sensitive data safe.
Does Markdown automatically improve retrieval quality?
No. It makes structure visible, but retrieval still depends on source quality, chunking, metadata, embeddings, ranking, and evaluation.
Related workflows
These links provide the next format, privacy, or review step for this specific guide.