Knowledge Base

Simple Definition

A knowledge base is an organized collection of information — documentation, policies, FAQs, product information, or any other content — that an AI system can access to answer questions.

In the AI context, a knowledge base is what you connect to an AI so it can answer questions about your specific business, product, or domain — rather than relying only on its general training.

Why You Need a Knowledge Base for AI

General-purpose AI like ChatGPT doesn’t know:

• Your company’s products, prices, or policies
• Your internal processes and documentation
• Information from after its training cutoff
• Proprietary or confidential business information

Connecting a knowledge base allows the AI to answer questions about your specific content accurately, using RAG (Retrieval-Augmented Generation) to pull in the relevant information.

What Goes Into a Knowledge Base

• Product documentation — manuals, specs, how-to guides
• FAQs — common questions and answers
• Policies — return policies, terms of service, HR policies
• Support content — troubleshooting guides, known issues
• Internal wikis — processes, team knowledge
• Research — reports, papers, competitive intelligence

Building AI on Your Knowledge Base

1. Collect and organize your documents
2. Process them into chunks (splitting long documents)
3. Create embeddings for each chunk
4. Store in a vector database
5. Connect an AI (via RAG) that retrieves relevant chunks to answer questions

Many tools simplify this process: Chatbase, Notion AI, Confluence AI, Intercom AI, and others.

Related Terms

• RAG — the technique for connecting a knowledge base to an AI
• Vector Database — where knowledge base embeddings are stored
• Embedding — how documents are converted for AI retrieval
• AI Assistant — often powered by a knowledge base for domain-specific Q&A