Ship features with the docs already written
Feature guides, onboarding flows, changelogs, and release notes that keep pace with the roadmap, without booking engineering time for every update.
The world's best product teams trust Documentation.AI
From next-gen start-ups to established enterprises.
Documentation is last on the launch checklist
Which is exactly why it is the first thing to slip.
- Release notes written last
- Usually on launch day, by whoever is free, reconstructed from a list of merged pull requests and a vague memory.
- Every edit needs an engineer
- A copy change queues behind a sprint, so the page stays wrong for two weeks because fixing it costs somebody a ticket.
- Onboarding content ages quietly
- The quickstart still walks through the flow you replaced two quarters ago, and support finds out before you do.
- Adoption stalls with no report filed
- Users who cannot find the guide rarely tell you. They just stop using the feature you spent a quarter shipping.
Turn what shipped into what is documented
Connect the repository and the issue tracker your team already works in, then edit drafts instead of starting pages from nothing.
- Connect GitHub or GitLab so the agent can read code files and recent commits
- Connect Jira so it queries issues with JQL, and Confluence so it reads your existing wiki
- Generate changelog entries from recent repository activity with a built-in workflow
- Run a documentation update after each merge, so feature changes arrive as proposed edits
- Publish feature overviews, onboarding flows, and release notes from the browser
- Review before anything ships: every run returns a summary, a report, and a commit
You keep editorial control throughout. The agent proposes and a person approves, which is the only arrangement that survives a launch week.
Documentation that moves with the roadmap
The signal already exists in the tools your team plans and ships in. These three read it.
Release notes with a source
The changelog generation workflow builds entries from real repository activity and documentation context, so the notes describe what changed rather than what somebody remembered on the day.
Context from where the work lives
Jira and Confluence connect as live context sources. The agent queries them at runtime through your OAuth connection rather than importing a snapshot that starts going stale immediately.
Proof the content is working
Analytics separates human views from AI agent views, ranks pages by engagement, and reports feedback and low-confidence assistant answers page by page.
What changes in the first sprint
One person connects the repository once. Everything after that is yours.
Workflows can trigger the moment a pull request merges, or run daily, weekly, or monthly.
GitHub, Jira, Confluence, and user feedback, selectable per workflow.
Publish a page, a changelog entry, or a whole section straight from the browser.
From signup to a live documentation site, with no credit card required.
“Documentation.AI has made it much easier for our product team to maintain documentation as our platform evolves. The AI Workflows, especially with Git repository context, help us keep our product and API docs closer to the actual product without adding extra manual effort.”
Frequently asked questions
What product teams check before they take documentation off engineering.
Do I need engineering to set this up?
One person connects the repository once. After that, product managers create workflows, edit pages, and publish from the dashboard without opening a ticket.
Will the agent publish something wrong?
It drafts, it does not auto-publish. Workflow runs produce a summary, a downloadable report, and a commit that a person reviews and merges.
Can we keep docs private until launch day?
Yes. Work on a branch with its own preview URL and merge when the feature ships. You can also gate individual pages, or the entire site, behind a password, JWT, or OAuth 2.0.
How is this different from a wiki?
A wiki stores whatever somebody wrote. Documentation.AI watches the repository and issue tracker your team already uses, proposes updates when they change, and publishes a fast, searchable site with an AI assistant on top.
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