AI Robot

An Internal Knowledge System with AI

Would you like colleagues to get quick answers to questions about products, policies, IT, processes, or customers? Then an internal knowledge system with its own chatbot is ideal. Thanks to Retrieval-Augmented Generation (RAG) this kind of system is smarter than ever: employees ask questions in plain language, and the chatbot searches your own documentation directly. This can be done completely securely, without leaking data to external parties – even if you use large language models from OpenAI or Google.

  • Does the answer always align with internal reality
  • Are no fabrications provided (as is sometimes the case with pure LLMs)
  • Are confidential data never shared with the outside world

Which tools can you use?

You can set up your own knowledge system using various products, depending on your preferences and requirements regarding privacy, scalability, and ease of use.

Chatbot and RAG frameworks

Vector databases (for document storage and fast search)

AI models

Important:
Many tools, including OpenWebUI and LlamaIndex, can connect both local (on-premises) and cloud-based models. Your documents and search queries never leave your own infrastructure unless you want them to!

How to add documents easily

Most modern knowledge systems offer a simple upload or synchronization feature.
For example, it works like this:

  1. Upload your documents (PDF, Word, text files, emails, wiki pages) via the web interface (such as OpenWebUI)
  2. Automatic processing: The tool indexes your document and makes it immediately searchable by the chatbot
  3. Live updates: Add a new file? It is usually incorporated into the answers within a few seconds or minutes

For advanced users:
Automatic connections to SharePoint, Google Drive, Dropbox, or a file server are easily possible with LlamaIndex or Haystack.

Data stays secure and internal

Whether you choose your own models or large cloud-based models:

  • You decide what is and is not shared externally
  • Integration with Single Sign-On and access management is supported by default
  • Audit trails: who has accessed what?

For sensitive information, it is advisable to use AI models on-premises or within a private cloud. But even if you use GPT-4 or Gemini, you can configure them so that your documents are never used as training data or stored permanently by the provider.

Example of a modern setup

With OpenWebUI you can easily build a secure, internal knowledge system in which employees can ask questions to specialized chatbots. You can upload documents, organize them by category, and have different chatbots act as experts in their respective fields. Read how here!

1. Add and categorize content

Uploading documents

  • Log in to OpenWebUI through your browser.
  • Go to the section Documents or Knowledge Base.
  • Click Upload and select your files (PDF, Word, text, etc.).
  • Tip: When uploading, add a category or label, such as “HR,” “Technical,” “Sales,” “Policy,” etc.

BenefitBy categorizing them, the right chatbot (expert) can focus on relevant sources, so you always receive an appropriate answer.

AIR via Open WebUI

2. Chatbots with their own areas of expertise (roles)

OpenWebUI makes it possible to create multiple chatbots, each with its own area of expertise or role. Examples:

  • HR Bot: Questions about leave, contracts, and employment conditions.
  • IT Support: Help with passwords, applications, and hardware.
  • PolicyBot: Answers about company policy and compliance.
  • SalesCoach: Information about products, prices, and quotes.

Get started right away or would you prefer help?

Want to run a proof of concept quickly? With, for example, OpenWebUI and LlamaIndex, you can often have a demo online in a single afternoon!
Want to set it up professionally, connect it to your existing IT, or make it genuinely secure?
NetCare helps with every step: from selecting the right solution to implementation, integration, and training.

Get in contact for a no-obligation consultation or demo.

NetCare – Your guide to AI, knowledge, and digital security

Gerard

Gerard works as an AI consultant and manager. With extensive experience at large organizations, he can quickly get to the heart of a problem and work toward a solution. Combined with his background in economics, this enables him to make sound business decisions.