Doxbrix is an AI-native documentation platform for teams that need to create, govern, publish, and improve knowledge at scale. It brings authoring, information a...
Doxbrix is an AI-native documentation platform for teams that need to create, govern, publish, and improve knowledge at scale. It brings authoring, information a...
Doxbrix is an AI-native documentation platform for teams that need to create, govern, publish, and improve knowledge at scale. It brings authoring, information architecture, collaboration, publishing, analytics, and reader support into one system so your documentation does not have to be split across a CMS, a docs site, and a separate AI layer.
In practice, that means one project can support the full lifecycle of a documentation site:
- authors draft and maintain content in the editor or in local files
- reviewers comment, suggest changes, and approve updates before release
- admins control branding, access, AI policy, and publishing settings
- readers search the site, browse structured navigation, and ask AI questions grounded in the published content
What Doxbrix helps you do
Who Doxbrix is for
Doxbrix is designed for mixed teams, not a single authoring persona. The same project can support several workflows at once:
| Team or role | Typical use in Doxbrix |
|---|---|
| **Technical writers** | Draft and maintain pages, manage structure, improve clarity, and run review workflows. |
| **Engineers** | Work in MDX locally, sync through the CLI or Git, and contribute through existing development workflows. |
| **Product and support teams** | Publish help-center content, track gaps through reader questions, and use the assistant to deflect common tickets. |
| **Developer relations or platform teams** | Combine conceptual guides, product documentation, and API reference pages in one site. |
| **Admins and documentation leads** | Manage branding, permissions, domains, AI policy, governance, and workspace-wide standards. |
One product, two authoring paths
- In the app — a visual editor with a block palette, AI writing help, quality scoring, review workflows, and analytics.
- As code — author Markdown/MDX locally and sync with the
dxbCLI and Git.
Both paths operate on the same underlying content model. A writer can update a page in the editor, while an engineer can work on the same documentation as MDX in a repository. Doxbrix is built so teams do not have to choose between a polished editing experience and docs-as-code discipline.
How the platform is organized
Doxbrix uses a deliberate hierarchy so both authors and readers can understand where information belongs. A workspace holds your team and shared settings. Each project is one documentation site. Inside a project, content is divided into spaces, which appear in the top navigation, and each space contains groups and pages in the sidebar.
This model matters because it affects everything else: routing, navigation, publishing, permissions, review, localization, and how the reader assistant finds answers.
See Core concepts for the detailed mental model, and Spaces & navigation for the navigation-building workflow.
AI is built into both authoring and reading
Doxbrix does not treat AI as a separate chatbot bolted onto a finished site. AI appears throughout the product in ways that map to real documentation work:
- For authors — a Writing Copilot drafts and continues content from the
/menu, Improve with AI rewrites a page to fix issues your quality scan flagged, and every page gets a live quality score across readability, structure, SEO, accessibility, and completeness. - For readers — an Ask AI assistant answers questions from your published content and cites the pages it used.
This separation is important: author-side AI helps your team produce better documentation, while reader-side AI helps your audience find answers faster without losing trust in the underlying content.
A typical Doxbrix workflow
Most teams adopt Doxbrix in the following order:
Start from a template or a blank project, then define the site name, slug, branding, visibility, editor mode, and language settings.
Create spaces for major sections, then add groups and pages to form a navigable structure that readers can scan quickly.
Authors write in the editor or in MDX, reviewers add comments and suggestions, and teams use approvals where required.
Publish pages or sections, monitor usage and quality, and improve weak areas with AI and analytics.
Let readers search, browse, and ask AI questions grounded in the content you have already approved and published.