A knowledge base that actually reduces tickets
Fast, searchable self-service backed by an AI assistant that answers with citations, plus the feedback signals that show you exactly which articles are failing your customers.
The world's best product teams trust Documentation.AI
From next-gen start-ups to established enterprises.
You know the docs are the problem. You cannot prove which page.
Ticket volume tells you something is missing. It never tells you what.
- The same question, twenty times a week
- Everyone on the team has a saved reply for it. Nobody has an afternoon free to turn the saved reply into an article.
- No signal on which article failed
- A customer who reads the wrong page and files a ticket anyway leaves no trace on the page that failed them.
- Articles drift after every release
- The product moved, the troubleshooting steps did not. Support is the first team to notice and the last to be told.
- Internal and customer knowledge live apart
- Escalation notes sit in one tool and public articles in another, and sooner or later the two contradict each other.
Close the loop between tickets and content
Documentation.AI reports which pages disappoint readers and which questions the assistant could not answer, then turns both into proposed fixes.
- See page-level satisfaction, likes, dislikes, and written comments in a sortable table
- Ask readers why after a thumbs down, using a short follow-up prompt you configure
- Review every question the AI Assistant was asked, where it was asked, and how confident it was
- Run the self-heal workflow to turn ratings, comments, and low-confidence answers into evidence-backed fixes
- Keep escalation notes and customer articles in one project, with the internal pages gated
- Export feedback and page data to CSV for the weekly review
The low-confidence answer list is the most useful queue you will get: it is the set of questions your customers ask that your documentation does not answer.
Deflection you can actually measure
Answering more questions is one half. Knowing which questions went unanswered is the half that compounds.
An assistant that cites its answer
Ask AI searches your published documentation and returns grounded answers with citations to the exact page and section, so a customer can verify the answer instead of opening a ticket to confirm it.
One project, two audiences
Partial access keeps most of the site public while gating internal pages behind a password, JWT, or OAuth 2.0, so your escalation runbooks and your public articles cannot drift apart.
Fixes with the evidence attached
The self-heal by user feedback workflow analyses page ratings, reader comments, and assistant confidence scores, finds the gaps, and proposes fixes backed by the evidence that identified them.
The questions your docs could not answer, on one list
- Answers cite the exact page and section, so a customer can verify and move on
- Every question is recorded with where on the site it was asked
- Low-confidence answers feed the self-heal workflow as evidence for a fix
What lands in your dashboard
Every number here is about the content, not about the queue.
Overview, Traffic, Feedback, and AI Assistant, each loading independently.
Every AI Assistant answer links the page and section it was drawn from.
Page-level feedback and page-specific detail, ready for the weekly review.
Public, partial, and private, so internal and customer content share one project.
“Documentation.AI helps us see what users are actually asking inside our docs, so we can identify gaps and improve our documentation more regularly.”
Frequently asked questions
What support leads ask before consolidating onto one platform.
How is this different from the knowledge base in our help desk?
A help desk stores articles. Documentation.AI reports which articles fail, which questions the assistant could not answer confidently, and runs a workflow that proposes fixes from that evidence.
Can we keep internal notes out of the public site?
Yes. Partial access mode keeps most pages public and gates the rest behind a password, JWT, or OAuth 2.0, page by page.
Does the AI Assistant make things up?
It answers from your published documentation and cites the page and section behind each answer. Answers carry a confidence score, and the low-confidence ones are listed for you to act on.
Can we see what customers were looking for?
Yes. Analytics covers search behaviour, page engagement, feedback, and every question asked of the AI Assistant, including where on the site it was asked.
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