PIPELINEGuide
What does an AI knowledge base cost? Factors, process, and funding options
There is no credible flat rate for an AI knowledge base — projects vary too much. What actually drives the effort, how you get to a concrete proposal, and which subsidies are available in Austria.
A flat rate for an AI knowledge base cannot credibly be quoted — it depends on the scope of the project, not the provider. Depending on the volume and condition of the documents. The actual proposal comes only after a short, non-binding initial conversation.
01 — Price
What it costs
- Price
- Individual based on effort
- Typical duration
- 6 to 10 weeks
Depending on the volume and condition of the documents. A fixed price can only be credibly quoted after the initial conversation — send us a brief outline of your project, and we'll send a proposal that fits the scope and effort.
02 — Factors
What drives the price
- Scope and number of integrations. Every additional system that needs to participate costs effort — regardless of how simple the core is.
- State of your starting point. Clean data, existing content and documented processes significantly reduce effort. Chaos is the most expensive cost factor.
- How much new material needs to be created. What you can contribute doesn't need to be invented by anyone. This is the biggest lever you have in your own hands.
- Requirements for design and customization. A solid standard system costs a fraction of a custom solution — and is sufficient more often than vendors admit.
- Operating model. One-time project costs or ongoing support: calculated over three years, this often gives a different picture than the quote comparison.
03 — Funding
Subsidies in Austria
For digitalization projects, there are several funding programs in Austria, such as KMU.DIGITAL or the aws digitalization funding. Whether and to what extent one of these is currently relevant for your project, we'll review with you individually. Current conditions: kmudigital.at, aws.at.
Which program is relevant, how high the subsidy currently is, and whether the budget for the current funding period is still open changes regularly — plus there are regional funding programs that vary by federal state. Only the information from the funding agencies themselves is reliable, not a fixed percentage stated here.
The most common mistake is always the same: commission first, then want funding. That doesn't work. Allow several weeks of lead time for application and approval.
04 — 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
05 — Questions
Frequently asked questions
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.
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.
How do we detect outdated answers?
Through date references and marking of documents flagged as obsolete. Analytics also show which sources are used most often — those you maintain 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.
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.
06 — Error
The most common mistakes
- Starting too big. Projects where nobody can use anything for months fail more often than average. A small, usable first step is almost always the better way.
- Not involving the people who work with it. Requirements that only come from management rarely match the actual work.
- Not defining a success measure. Without a metric defined in advance, you can't say afterwards whether it delivered anything — and the next decision will be made on gut feeling again.
- Overlooking operating costs. The project price is only part of it. What operation costs over three years belongs in the same calculation.
- Creating dependency. If you don't get access, documentation and source code, you're locked in. That needs to be clarified before commissioning, not after.
07 — Next
Related pages
- AI Knowledge Base — Overview
- AI Knowledge Base — Team and Acceptance
- AI Knowledge Base — Implementation
- AI knowledge base — integration
- AI knowledge base — where to start
- AI knowledge base — AI disclosure
- AI knowledge base — alternatives
- AI knowledge base — risks
- AI automation
- Document processing with AI
- AI chatbot
- All guides
Next step
Initial assessment, no obligation.
Briefly describe what you need. You'll get an honest answer about what's realistic and what it will roughly cost.