Knoku

Knoku connects to a team’s existing documentation sources and builds a unified cited index that answers user questions through an embeddable chat widget, a Slack integration, and a REST API. The core workflow is point-and-index: crawl a public docs site on a schedule, sync Markdown from a GitHub repo on each commit, pull runbooks from Notion or Confluence, or upload PDFs directly. Answers surface with citations linked back to the originating source file, so the tool functions as a retrieval layer over content teams already own rather than a new content system.

The differentiating feature is the gap analytics layer. Rather than logging queries into a void, Knoku tracks which questions went unanswered — meaning no source contained a confident match — alongside deflection counts by channel and traffic patterns by source. Teams use this to identify which docs pages to write next, without exporting support data into a separate BI tool.

Knoku fits SaaS teams whose documentation already exists and whose support load is dominated by questions the docs technically answer. It breaks when the underlying docs are thin, inconsistent, or poorly structured — retrieval quality is bounded by source quality, and no amount of indexing fixes a knowledge gap. The tool also hits a wall for teams with compliance requirements that prohibit external query processing, since there is no self-hosted deployment path. Teams with those constraints typically route to open-source retrieval stacks they can run on their own infrastructure.

Integration coverage includes GitHub Discussions, Issues, and PRs in addition to Markdown files; Jira tickets for known issues and release context; Zendesk Help Center sections; and hosted OpenAPI or Swagger schemas so the assistant can answer endpoint-level questions. All source types feed the same index, and each answer carries a citation to the specific file or ticket it drew from.