How can users chat with a knowledge base?

Chatting with a knowledge base means allowing users to ask questions and receive direct answers from documented information instead of browsing pages or searching manually. The answers come from the knowledge base content itself, such as documentation, help articles, or internal guides.

Why traditional knowledge bases are hard to use

Traditional knowledge bases rely on navigation menus or keyword search. Users need to know where information is located or how to phrase search terms correctly. Even when answers exist, they can be difficult to find quickly.

As a result, users often leave the knowledge base and contact support instead of finding answers on their own.

How chat-based access to a knowledge base works

Chat-based access works by retrieving relevant information from the knowledge base when a question is asked. Instead of returning a list of pages, the system generates a direct answer using only the retrieved content.

This approach is explained in how Chatref works and is based on retrieval-augmented generation, which focuses on accuracy rather than open-ended conversation.

Step-by-step: chatting with a knowledge base

Step 1: Use existing knowledge base content

The process begins with the knowledge base content you already have. This can include help articles, documentation, FAQs, or internal guides. No restructuring or rewriting is required.

This same content is often used when making documentation searchable with AI.

Step 2: Structure content for retrieval

Once connected, the content is broken into smaller sections so specific information can be retrieved when a question is asked. Context such as headings and source location is preserved.

This retrieval-first approach is why retrieval-augmented generation is used instead of basic search.

Step 3: Users ask questions in natural language

Users can ask questions using everyday language without needing to navigate menus or guess keywords. Questions can be phrased in different ways and still retrieve relevant information.

This experience is similar to turning FAQs into a chatbot, but applied to broader knowledge base content.

Step 4: Relevant answers are generated

When a question is asked, the system retrieves relevant sections of the knowledge base and generates an answer based only on that information. Irrelevant content is ignored.

This approach differs from general AI chat systems often discussed on the comparison page, which may generate answers without checking a specific source.

Accuracy and boundaries

Answers are generated strictly from the connected knowledge base. If the knowledge base does not contain the requested information, the system does not guess or invent answers.

This ensures that the knowledge base remains the single source of truth.

Where chat-based knowledge access works best

Chatting with a knowledge base works best for:

  • Product documentation
  • Help and support centers
  • Internal team knowledge
  • Policy and process references

It is less effective when information is not documented or requires personal judgment.

What happens when the knowledge base does not contain an answer?

If the knowledge base does not include the information needed to answer a question, the system responds by indicating that the answer is not available. It does not attempt to infer or generate speculative responses.

This behavior is explained further in the FAQ.

Summary

Users can chat with a knowledge base by asking questions in natural language and receiving answers generated strictly from documented content. This improves access to information, reduces support requests, and ensures accurate responses without hallucinations.

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