How to train an AI chatbot on your documentation

Pick the source of truth

Index the public docs origin, help center, or sitemap — not the marketing homepage. If you only need /docs or docs.example.com, say so. Marketing copy, login shells, and outdated blog posts share keywords with the real answer and pollute retrieval.

Make pages retrievable

Use one topic per page, a heading that matches customer language, a direct answer near the top, and stable URLs. Split giant guides. Add examples next to the rule they illustrate. Retrieval fails when the fact is buried in a 4,000-word overview.

Test before you embed

Use ten questions from real tickets. Include two the docs do not cover. A ready chatbot cites the correct page on covered questions and declines the rest. If it invents an endpoint or last year's price, fix the source or the crawl before going live.

Recrawl is part of training

Documentation changes when you ship. Re-index after releases, pricing updates, and API migrations. A chatbot trained once is a chatbot trained on last quarter. Prefer daily or on-demand sync over a one-shot upload.

How usedocs helps

usedocs crawls docs or files, lets you test cited answers in the dashboard, embeds with one script tag, and turns refused questions into a gap list you can draft and publish.

FAQ

Do I need to fine-tune a model?

Usually no. For product support, retrieve the right documentation chunks and constrain the answer to those sources.

Can I train on PDFs?

Yes if the text extracts cleanly. Prefer HTML docs with headings and URLs when you have the choice.

How much documentation is enough?

Enough to cover the questions customers already ask. Launch on that set, then write the missing pages the chatbot exposes.

Use usedocs for this

usedocs crawls your docs site or files, answers with citations, and shows you which pages failed real visitor questions.

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