Your AI companion for DocsBot AI.

A confident answer still needs a source that earns it.

A bot can sound helpful while relying on stale wording or filling a gap with a plausible guess. The quality test is whether the answer is supported by the documentation the team actually wants customers to trust.

Strawberry can test DocsBot AI answers against the linked sources and prepare a clear list of supported, weak, and unsupported responses.

The knowledge base is part of the product surface.

Duplicated articles, conflicting policies, and missing setup steps do not stay inside documentation. They surface as inconsistent answers and customer uncertainty.

Use Strawberry to compare the DocsBot AI source set with the documentation tabs you select, then prepare a cleanup proposal that someone can approve deliberately.

Failed answers are a more useful backlog than generic chatbot feedback.

“Improve the bot” does not tell the documentation team which question failed, who it affected, or whether the answer needs a new article, a product fix, or a policy decision.

Strawberry can turn the DocsBot AI conversations you review into evidence-backed backlog items with a clear proposed owner.

Answer quality benefits from a recurring reality check.

Every two weeks, Strawberry samples DocsBot AI conversations against the current documentation and groups hallucinations, stale answers, and uncovered topics for review. Changing the bot or its sources from an unreviewed sample can make a bad answer repeat across customer conversations.

Frequently asked questions