PIPELINEGuide
AI knowledge base: process, approach, and what's needed from you
The process for an AI knowledge base from the first question to ongoing operation — including what you need to contribute to make it work.
An AI knowledge base project runs in 4 steps: from “define sources” to “rollout,” 6 to 10 weeks total. Each step ends with a clear approval before the next one begins.
01 — Process
The steps in detail
Define sources
Which repositories go in, which stay out. Usually less is more.
Clarify permissions
The permissions model from your systems is adopted, not reinvented.
Index and test
We test with real questions from your business and measure whether the right documents are found.
Rollout
Start with one department, then expand. The analytics show where documentation is missing.
02 — Participation
What we need from you
- A contact person who can make decisions — not just forward them.
- Access to the affected systems, in time and not on launch day.
- Real examples from daily business — the messier, the more useful for testing.
- Two to four hours for coordination, distributed over the project duration.
- An answer to the question of what success means. Without it, nothing can be assessed afterward.
03 — Scope
What's included
- Indexing your repositories: file servers, SharePoint, Google Drive, Confluence, email archives
- Answers with source references and jump to the original document
- Permissions model — who can see what also applies to search
- Detection of outdated documents to prevent obsolete answers
- Analytics on what questions are asked and where documentation is missing
- Hosting either in the EU cloud or on your own infrastructure
04 — Questions
Frequently asked questions
What is RAG?
The abbreviation stands for retrieval-augmented generation. Instead of having the language model answer from memory, your documents are searched first, and only the passages found are used to generate the answer. That's why the answer has a source.
How long does setup take with a large document base?
It depends less on volume than on condition: well-structured repositories with few duplicates are ready in a few weeks, grown repositories with many old versions need a cleanup round first.
Our documents are a mess. Will it still work?
To a certain extent, yes — the system handles different formats and structures. What it cannot do is resolve conflicting information. If three versions of a price list are in circulation, you need to clarify which one applies first.
Can we roll this out to more departments step by step?
Yes, that's the usual approach. Start with one department, learn from their questions and results, then connect the next one — rather than releasing everything at once.
Will everyone see everything?
No. The permissions from your existing systems are carried over. If someone isn't allowed to open a folder today, they won't get answers from it either.
What if we have multiple languages in our document base?
No problem — the search understands questions and documents regardless of language and finds the right answer even when the question and source are written in different languages.
Does this have to run in the cloud?
No. For sensitive areas, we use models that run entirely on your own hardware. That costs more to set up and slightly reduces answer quality, but no document leaves the building.
05 — Decision
How to move forward
The most affordable next step is a conversation, not a quote. Twenty minutes is usually enough to clarify whether a project makes sense, what scope it involves, and whether we're the right fit.
If we're not, we'll say so. An honest no costs less than a project you abandon after three months — for both sides.
06 — Next
Related pages
- AI Knowledge Base — Overview
- AI knowledge base — AI disclosure
- AI knowledge base — checklist
- AI knowledge base — viability
- AI Knowledge Base — As of 2026
- AI knowledge base — alternatives
- AI Knowledge Base — Small Businesses
- AI knowledge base — where to start
- AI automation
- Document processing with AI
- AI chatbot
- All guides
Next step
Let's talk briefly about whether this makes sense for you.
A twenty-minute conversation is usually enough to clarify whether a project makes sense. If not, we'll say so — that's cheaper for both sides than an offer nobody needs.