The answer is already somewhere. In the quality manual, an old email or the folder only one colleague knows about. Yet your team spends every day looking for it again.
With AI knowledge management, employees can ask directly: “What approval do I need for this order?” The system finds the relevant passage in your documents and gives a clear answer with a source. Your team moves forward while the documents stay where people already work with them.
This pays off wherever the same questions keep landing with the same people: customer service, onboarding, sales or administration. The first decision is how much of a system you actually need.
Which solution fits your business?
An existing AI tool is often enough to get started. If your team already uses ChatGPT at work and the sources you need are supported, Company Knowledge in ChatGPT Business, Enterprise or Edu can make existing knowledge accessible. The permissions and settings of the connected sources still apply. Check this option before buying another set of tools. Company Knowledge at OpenAI.
A knowledge platform fits when you want a ready-made application. Search, source management and team use are the focus here. What matters is whether the platform can handle your repositories, permissions and operating requirements. A convincing trial uses your own questions and documents.
A custom solution pays off when knowledge becomes part of a specific workflow. For example, when an answer belongs directly in your business application, several systems need to work together or an approved result should trigger the next step. We develop and integrate the system around the way your business works.
The practical sequence: check what you already have, test it in a real workflow, then add what is missing. That puts your budget into results for your team.
Three things a good knowledge system must do
Find the right source. Your team needs the current work instruction, not a similar-sounding PDF from three years ago. A good system connects existing repositories and keeps its search index current. The original remains the authoritative source.
Make the answer verifiable. “According to the manual” is little help. A link to the right section is useful. Employees can check the statement immediately and read the source themselves for important decisions. If the documents do not support a reliable answer, that must be clear.
Respect permissions. Anyone who cannot open the original document should not learn its contents through AI. Access rights must therefore limit which sources are selected in the first place. A friendly answer interface alone cannot solve this.
How your documents become an answer
The system makes your existing sources searchable, such as SharePoint, a wiki or a file server. When someone asks a question, it retrieves the relevant passages and passes them to a language model. The model uses them to compose an answer and points back to the sources. This method is called retrieval-augmented generation, or RAG.
Your company knowledge does not need to be trained into a model. Source quality, search and the handling of conflicting or missing information are what matter. The model running in the background is one part of the solution.
Test the questions that cost you time today
Start with one department and the questions that keep coming up there. Give the system real documents and review the results with the people who use them:
- Does it find the right, up-to-date information?
- Does the answer cite a specific source?
- Do confidential contents remain inaccessible to unauthorised users?
- Does the answer help someone complete the next task faster?
Include a question the documents cannot answer. This is where you see whether the system behaves reliably.
Hosting, data processing and ongoing operation belong in the decision from the start. We integrate suitable existing tools or build the connections you need, with clear roles and controlled data flows. Explore our solutions for knowledge management and internal assistants.
From the first workshop to knowledge in daily use
At Kirsch & Drechsler, an opportunity assessment and workshops grew into an ongoing partnership: internal knowledge management, a website chatbot and joint development of CherryGate. It shows how individual AI ideas can grow into a foundation the company keeps using. See our work with Kirsch & Drechsler.
Ready to introduce this to your team? Our internal AI assistant service covers source integration, access controls, testing and team introduction.
