English AI & Project Delivery
How to build an AI knowledge base from internal company documents
A practical plan for document preparation, RAG retrieval, access control, citation checks and updates.
The short answer
An internal knowledge assistant usually organizes authoritative documents and uses retrieval-augmented generation (RAG) to supply relevant context. Access, citations, updates, deletion and acceptance testing are part of delivery; file upload alone is not completion.
Define users and questions first
Choose a concrete task, such as internal product lookup or presales document retrieval. List common questions, permitted sources and who resolves missing or conflicting information. An employee assistant and public support assistant should not automatically share all material.
Prepare documents before designing retrieval
RAG retrieves external material to provide context before generation; it is not permanent training on every uploaded file. Check readability of PDFs, spreadsheets and scans, retain versions and locations, then plan chunking, retrieval and reranking. Sample cross-page tables and important text embedded in images.
| Check | What to establish |
|---|---|
| Documents | Authoritative versions, formats and an update owner |
| Access | Retrieval scope and citation permissions |
| Acceptance | Representative questions, missing-answer handling and citation checks |
Check access during retrieval and display
For department or project restrictions, retrieval must follow user identity rather than merely hide interface controls. Citation links should respect source permissions. Removing an obsolete document also requires checking indexes, caches and subsequent answers for stale versions.
Test representative questions, not a single demo
Build cases covering answerable questions, missing material, access restrictions, version conflicts and false premises. Assess document retrieval, answer support and citation locations separately. These are implementation recommendations; do not promise accuracy without measured results.
Include maintenance and costs in scope
Specify document volume, update frequency, authentication, user interface and external integrations. Assign model, document processing, storage, hosting and maintenance costs. Start with a bounded pilot and use acceptance results to decide expansion; agree prices and schedules against actual conditions.
A project checklist
- Documents: Authoritative versions, formats and an update owner
- Access: Retrieval scope and citation permissions
- Acceptance: Representative questions, missing-answer handling and citation checks
Common questions
Is fine-tuning required first?
Not necessarily. Establish whether the task needs current retrieved evidence before evaluating retrieval, prompting or fine-tuning.
Can scanned PDFs be used directly?
Check OCR and layout extraction quality, and sample important tables and numbers.
Can every question be answered?
No. Missing authoritative evidence should lead to an explicit uncertainty response or human handoff.
What should I bring to a scoping discussion?
Bring sanitized samples, questions, approximate user scope and access requirements. Avoid sending sensitive source documents through an ordinary enquiry form.
References and editorial notes
Definitions refer to the documentation below. Planning steps and checklists express Ones Laboratory’s recommendations. Sources checked on 2026-10-23.
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