What is an AI knowledge base?
An AI knowledge base is a collection of an organisation's content indexed by meaning rather than by keyword, so a question can be answered from the relevant passage directly instead of returning a list of documents to read.
A traditional knowledge base stores articles and gives you search over their words. An AI knowledge base stores the same content as passages indexed by meaning, which is what allows a question phrased in the customer's own words to reach the passage that answers it.
Why it matters
Most help centres already contain the answer to the questions they get asked. What fails is retrieval: the customer describes a problem and the search box matches on vocabulary they did not use. Indexing by meaning removes the requirement that the asker guess the author's wording, which usually raises the usefulness of documentation you already wrote without writing any more of it.
Examples
- Product pages, policy pages and help articles indexed together so an answer can come from whichever one holds it.
- A support team's saved replies added as a source alongside published pages.
- A gaps list showing which asked-about topics have no passage covering them.
Not the same as
Help centre
A help centre is the published articles themselves. An AI knowledge base is the index built over them — and can index far more than the help centre, including product and policy pages.
Vector database
A vector database is the storage layer that holds the embeddings. The knowledge base is the content, the chunking and the retrieval behaviour built on top of it.
Related
tool
Website knowledge base generator
Reads your website and organises it into a knowledge base structure — topics, the pages that belong to each, and the topics customers ask about that your site doesn't cover. Exports as Markdown.
tool
Website content analyzer
Audits your website's content the way a support lead would: which customer topics are covered well, which pages are too thin to answer from, and which standard topics are absent.
term
What is a knowledge base?
Traditionally a knowledge base is a help centre humans read. For AI support it is the source material a representative answers from — which means an ordinary website, well written, can serve as one without a separate help centre.
term
What is an embedding?
Embeddings are why an AI representative can answer "do you deliver to Berlin?" from a page that only says "we ship across the EU". Text is converted to vectors, and similar meaning lands close together.
term
What is chunking in AI retrieval?
A whole page is the wrong unit to retrieve. A returns policy page might cover eligibility, timing, refunds and exchanges; retrieving all of it to answer one question about timing buries the relevant sentence in three paragraphs of noise. Chunking splits it so that each part can be found on its own. The split usually follows paragraph or heading boundaries, because those are where a human author already decided one idea ended and another began.
term
What is a vector database?
Comparing a question to every stored passage is exact and gets slower in proportion to how many passages there are. A vector database trades a little accuracy for a large speed gain by building an index that skips most of the comparisons. That trade is worth making at millions of vectors and is close to pointless at thousands.
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