Detect and fix stale documentation
AI-drafted answers from real user questions.
The product ships weekly but the docs do not, and nobody owns noticing the drift. Users follow outdated instructions, fail, and lose trust in the entire docs site — which drives even more tickets.
Kelu's doc proposals scan knowledge gaps and draft answers to close them; your team reviews and accepts or dismisses each proposal. Combined with scheduled source syncs that keep the index current, docs maintenance becomes a review queue instead of an archaeology project.
How it works
- 01
Scheduled syncs keep the index matched to your current docs.
- 02
Gap analytics reveal where users' questions and your docs have drifted apart.
- 03
Doc proposal scans draft Q&A answers to close those gaps.
- 04
Your team reviews each proposal and accepts or dismisses it.
What you get
- Turn docs maintenance into a review queue instead of an archaeology project.
- Catch drift from real user questions instead of waiting for angry tickets.
- Keep the AI's index current automatically as docs and repos change.
- Ship new answers with AI drafting and human judgment.
Features that make it work
Got questions?
Frequently asked questions
How does Kelu know a doc is stale?
Staleness shows up as unanswerable or poorly answered questions: gap analytics flag topics where user questions outpace your content. Doc proposal scans then draft content to close the specific gaps found.
Does the AI publish doc changes on its own?
No. Proposals sit in a review queue where your team accepts or dismisses each one. Nothing changes in your docs without human approval.
How current is the AI's view of our docs?
As current as your last sync — sources re-index on a schedule, and GitHub sources re-index via webhook on push, so the assistant answers from the docs you actually ship.
How long does setup take?
Most teams are live the same day. You connect a source — a docs URL, GitHub repo, Notion workspace, or a file upload — and Kelu crawls, normalizes, chunks, and embeds the content automatically. The website widget is a single script tag, and the Slack bot installs in a few clicks. There is no model to fine-tune and no infrastructure to run.
Are answers backed by citations?
Yes. Every answer from your docs includes a structured citations list with the URL, title, and excerpt of each source used, and the answer text cites sources inline. Users can click through to verify any claim against the original document — which is what makes the answers trustworthy enough for support, sales, and internal use.
Is my content used to train AI models?
No. Your indexed content, embeddings, and conversations are isolated to your workspace and are only used to answer your own questions. Content is never shared across customers, and data is encrypted at rest and in transit. Enterprise plans add OIDC/SAML SSO, a widget without Kelu branding, and a custom SLA.
Which knowledge sources can I connect?
24 source types: websites, GitHub (docs files, source code, issues, pull requests, discussions), Notion, Confluence, Google Drive, OneDrive, Zendesk (Help Center and solved tickets), Jira, Jira Service Management, Linear, Salesforce Knowledge articles, Salesforce Cases, Discourse, Stack Overflow for Teams, YouTube, OpenAPI specs, S3, curated Q&A, and direct file uploads (PDF, DOCX, XLSX, CSV, Markdown, TXT, HTML). Sources sync on a schedule, and GitHub sources can re-index automatically via webhook on every push.
What happens when the AI is not confident in an answer?
Answers are grounded in your sources. When they do not cover a question, Kelu returns a transparent, configurable fallback — typically pointing users to your support channel — instead of guessing. Those unanswered questions are logged in knowledge gap analytics so you can close the gap in your docs.
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