PIPELINEGuide
AI knowledge base: using funding in Austria
For digitalization projects like AI knowledge base, there are several funding programs in Austria. Which ones are relevant, which deadlines to observe, and where the most common mistake lies.
For digitization projects, Austria offers several funding programs, such as KMU.DIGITAL or the aws digitization funding. Whether and to what extent one of these currently applies to your project, we'll review individually with you. Current terms: kmudigital.at, aws.at. In any case, the sequence is crucial: first the approved application, then the order for AI knowledge base.
01 — 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.
02 — 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.
03 — Process
How a funding application works
Check funding program
Which program fits the project and company size. This determines the subsidy amount and effort.
Obtain quote
A quote is usually required for the application — commissioning does not happen yet.
Submit application
Submission with project description, cost breakdown and schedule.
Wait for approval
Only after approval is the commission placed. If you commission earlier, you lose the funding.
Implement and settle accounts
After completion, final accounting with supporting documents follows.
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.
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.
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 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.
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.
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 — Next
Related pages
- AI Knowledge Base — Overview
- AI knowledge base — process
- AI Knowledge Base — Team and Acceptance
- AI knowledge base — checklist
- AI knowledge base — common mistakes
- AI knowledge base — timeline
- AI Knowledge Base — DIY
- AI knowledge base — practical examples
- 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.