Do you want colleagues to get quick answers to questions about Products, policy, IT, processes, or customers? Then an internal knowledge system with its own chatbot is ideal. Thanks to Retrieval-Augmented Generation (RAG), such a system is smarter than ever: employees ask questions in plain language and the chatbot searches directly in your own documentation. This can be done completely securely, without leaking data to external parties – even if you use large language models from OpenAI or Google.
RAG means that an AI chatbot first searches your own knowledge source (documents, wikis, manuals, policies) and only then generates an answer. This ensures that:
The answer always aligns with the internal reality
No fabrications are given (as sometimes happens with pure LLMs)
Confidential data is never shared with the outside world
Setting up your own knowledge system can be done with various products, depending on your preferences and requirements for privacy, scalability, and ease of use.
LlamaIndex (llamaindex.ai) – Open source, widely applicable
Haystack (haystack.deepset.ai) – Strong in enterprise search
LangChain (langchain.com) – Powerful for integrations and customization
OpenWebUI (open-webui.github.io) – Simple, modern web interface for chat and management
ChromaDB (trychroma.com)
Weaviate (weaviate.io)
Qdrant (qdrant.tech)
Large models in the cloud
Own models (on-premises or private cloud)
Important:
Many tools, including OpenWebUI and LlamaIndex, can connect both local (on-premises) and cloud models. Your documents and search queries never leave your own infrastructure, unless you want them to!
Most modern knowledge systems offer a simple upload or synchronization function.
This works, for example, as follows:
Upload your documents (PDF, Word, txt, emails, wiki pages) via the web interface (like OpenWebUI)
Automatic processing: The tool indexes your document and makes it immediately searchable for the chatbot
Live updating: If you add a new file? It is usually included in the answers within seconds or minutes
For advanced users:
Automatic connections with SharePoint, Google Drive, Dropbox, or a file server are easily possible with LlamaIndex or Haystack.
Whether you choose your own models or large cloud models:
You decide what goes out and what doesn’t
Integration with Single Sign-On and access control is standardly possible
Audit trails: who 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 set it up so that your documents are never used as training data or permanently stored by the provider.
With OpenWebUI, you can easily build a secure, internal knowledge system where employees can ask questions to specialized chatbots. You can upload documents, organize them by category, and have different chatbots act as experts in their own field. Here’s how!
Log in to OpenWebUI via your browser.
Go to the Documents or Knowledge Base section.
Click Upload and select your files (PDF, Word, text, etc).
Tip: Add a category or label when uploading, such as “HR”, “Technology”, “Sales”, “Policy”, etc.
Advantage: By categorizing, the right chatbot (expert) can focus on relevant sources and you always get a suitable answer.
OpenWebUI makes it possible to create multiple chatbots, each with its own specialism or role. Examples:
HR-Bot: Questions about leave, contracts, terms of employment.
IT-Support: Help with passwords, applications, hardware.
PolicyBot: Answers about company policy and compliance.
SalesCoach: Information about products, prices, and quotes.
Want to quickly run a proof-of-concept? With, for example, OpenWebUI and LlamaIndex, you often have a demo online in one afternoon!
Want to set it up professionally, connect it to your existing IT, or does it need to be truly secure?
NetCare helps with every step: from choosing the right tools to implementation, integration, and training.
Contact us for a free consultation or demo.
NetCare – Your guide to AI, knowledge, and digital security