AI knowledge base in service
Example: Ask your manuals and service knowledge with AI.
Your service team asks in their own words and gets the answer from manuals and service documents, with the source to check. This example shows how an internal AI knowledge base works day to day.
PDFs, Wikis, Projects
Everyone sees only what they may
+
AI
to check
checks important points against the original
A short explanation
Answers from the manual
Find product knowledge with sources. Missing or outdated information stays visible.
English · about 1 minute · with captions
Our own development · Sample data
One question. One answer. The relevant source.
For example, ask: “What maintenance interval applies to P200?” The demo shows a draft answer with sources you can open directly.
The product and service documents use illustrative data. They demonstrate knowledge search and show how missing or conflicting information remains visible.
How it works
From the example to your pilot.
One team, one knowledge area, for example up to 50 documents and 30 test questions. Then you decide: expand, improve or stop.
01
Collect questions
Which questions does your team ask again and again? And where is the answer?
02
Check documents
What is current, and who may see what? Outdated material stays out.
03
Build and Test the Pilot
We build the knowledge base and check it with your test questions: are the answer, the source and the access rights correct?
04
Decide
Expand, improve or stop. You decide based on the test results.
Is this right for you?
A knowledge base pays off when …
Frequency
… your team often answers the same questions
Questions about products, processes or service cases keep coming back and cost time every day.
Documents
… the answers are spread across many documents
Your team regularly searches manuals, files and internal storage.
Upkeep
… someone keeps the content up to date
A responsible person checks the sources and makes sure changes are added.
Who is behind it
Advice and delivery from one source.
You talk to the person who actually builds your knowledge base.
Client project · in use
AI knowledge assistant for APIORIUM
A multilingual website chatbot with its own knowledge base answers questions about services, locations and products.
Personal
Martin Trixner
Has been building software and integrations since 2002 and is a certified AI-Automations-Manager.
For your team
Internal, with sources and access rights
For your internal knowledge base, source references, access rights and the connection to your file storage are added.
Frequently Asked Questions
Frequently asked questions about the AI knowledge base in service.
How do we know the answers are right?
The answers name their sources so they can be checked. In the pilot we use your test questions to check whether answer and source are correct and how the system handles missing or contradictory information.
Who sees which documents?
Which documents go in and who may see what is agreed before the start. Confidential material is only available to authorised people. We check this before it goes into use.
Can the same knowledge base prepare quotes?
Yes, if it contains product information and earlier solutions. It then supplies suitable products and open questions. Prices, quantities and discounts come from fixed rules and your systems, not from the AI. Your team reviews and approves.
What does it cost?
That depends on the volume and type of documents, the number of users and the integrations. After reviewing your documents you receive a written quote, with implementation and operation shown separately.
Next Step
Which questions should your knowledge base answer?
Bring three typical questions and a description of your documents. In a free discovery call with Martin Trixner, we assess whether a pilot makes sense and what preparation it needs.