Quellwerk: An AI-powered knowledge database for your company's knowledge
What circumstances make an AI knowledge base necessary in the first place?
Mid-sized industrial companies with expertise in design, manufacturing, or services often store this knowledge in silos: memos, email threads, and the experiential knowledge of individual employees. When a key knowledge holder leaves - whether due to vacation, illness, or retirement - this knowledge is lost in whole or in part; it takes new employees a long time to become productive because the necessary expertise cannot be found in a centralized location. Out-of-the-box AI systems like ChatGPT or Claude are not aware of this internal knowledge - they only respond to information that is publicly available or included in the respective prompt. We therefore describe the following analysis in terms of products and concepts, rather than as a case study of a specific company.
What problem does Quellwerk solve, and who stands to benefit from it?
For decision-makers, the question is this: How much work time is lost when experienced employees have to repeatedly answer the same questions from colleagues or new team members? How high is the risk that knowledge will be irretrievably lost when a single person leaves the company? And is it worth the effort to feed internal knowledge into an AI if standard AI tools aren’t familiar with that knowledge anyway? This is exactly where Quellwerk comes in: as a knowledge database that structures company knowledge in a way that allows AI to generate answers from it and turns every answered question into new, reusable knowledge. For your project, this means: The business case isn’t based on a single feature, but on the combined benefits of reduced onboarding time, a lower risk of knowledge loss, and fewer recurring internal inquiries.
How does Quellwerk's approach work, without getting into the technical details?
We have set up Quellwerk as a loop: A department - such as Sales, Customer Service, Manufacturing, or Assembly - asks a question. The AI assistant searches the department’s wiki (standards and guidelines, components and assemblies, design knowledge, previously approved answers) and drafts a response. An expert employee from the department reviews this draft and approves it - only then is the answer sent back to the requesting department and simultaneously saved as a new wiki entry. Human approval is not an optional extra, but an integral part of our process.
Furthermore, knowledge is never deleted; instead, it is marked as outdated when necessary, with a link to the successor entry - making it traceable rather than lost. If an external condition changes - such as a law or a funding program - the system flags the affected entries for revision. In our assessment, the majority of companies in our target market use Office 365 for email and calendars - this environment can also be integrated as a knowledge source for the wiki if needed, so that emails and calendar entries are incorporated. We offer the service either as a cloud-based solution, behind your firewall, or with an on-premises model in Germany - GDPR-compliant, with no data transfer to the U.S. We always sell Quellwerk in conjunction with a workshop, during which we first analyze your existing knowledge management process and only then automate it. For your project, this means: You decide on the operating mode and scope of implementation before automation begins - not after.
Where are the true limits of Quellwerk?
We do not use Quellwerk as a substitute for expert review: Every AI-generated response undergoes human approval before it is sent back and incorporated into the wiki - this takes time, especially in the initial phase, and is a deliberate design choice on our part rather than relying on fully automated responses. The benefits also depend on how much knowledge is already available in a structured format and how consistently departments maintain the process - a software tool alone, without an accompanying workshop and active use, does not add any value. Furthermore, since no customer project has been completed to date, we cannot provide any empirical data from live operations at this time.
At what point does it become worthwhile for your company?
In our view, an AI knowledge base like Quellwerk tends to be worthwhile when several factors align: recurring, similar technical questions across multiple departments or locations; a noticeable risk of turnover or an aging workforce among key knowledge holders; and a knowledge base that is large enough that searching through it already takes time today. Without a completed project, this criterion remains qualitative for us at this time.
What happens next?
If recurring internal questions, onboarding time, or the risk of knowledge loss are causing a noticeable burden in your company, a no-obligation consultation is the next logical step: Together, we’ll first review your existing knowledge management process, and only then will we decide together whether - and at which level (Basic or Enterprise) - an AI-powered knowledge base would be a worthwhile investment for you.
FAQ
What data leaves my company when using Quellwerk? That depends on the operating mode you choose - cloud, behind your firewall, or a local model in Germany. In all cases, we operate in compliance with the GDPR, without any necessary data transfer to the U.S.
Do I have to implement Quellwerk without a workshop? No. We generally only sell Quellwerk in conjunction with a workshop, during which we first analyze your existing knowledge management process.
Does Quellwerk replace the expert review by employees? No. Every AI-generated answer undergoes mandatory human approval before it is sent back and incorporated into the wiki.
More information at https://quellwerk-ki.com/en