# Documentation.AI

> Create and maintain world-class documentation built for both humans and AI. The AI native documentation and knowledge platform.

Documentation.AI is a documentation and knowledge base platform. Teams write in a web editor or in Markdown/MDX through Git, publish a fast branded site, and use built-in AI to keep pages accurate, answer reader questions in context, and stay citable by AI search.

This file indexes documentation.ai. Product documentation is a separate application served under /docs on this same host and publishes its own index at https://documentation.ai/docs/llms.txt, where every page is also available as Markdown by appending .md to its URL.

## Product

- [Documentation.AI](https://documentation.ai/): Home. What the platform does: AI-native documentation and knowledge base software, the AI agent that keeps docs current, Ask AI search, and analytics
- [Solutions](https://documentation.ai/solutions): Directory of the eleven solution pages below, grouped by team and by use case, plus what is true of all of them
- [Pricing](https://documentation.ai/pricing): All four plans with per-feature comparison: free tier, seats, AI usage limits, private docs, authentication, and analytics
- [Customers](https://documentation.ai/customers): Index of customer case studies
- [About](https://documentation.ai/about): What the company is building and how the team works

## Solutions

- [Technical Writers](https://documentation.ai/solutions/technical-writers): Structure, write, review, and publish documentation in one platform, with an AI agent that handles the maintenance work for you.
- [Product Managers](https://documentation.ai/solutions/product-managers): Feature guides, onboarding flows, changelogs, and release notes that keep pace with the roadmap, without booking engineering time for every update.
- [Developers](https://documentation.ai/solutions/developers): Markdown and MDX in your own editor, branches and pull requests, preview builds on every PR, and API references generated from your OpenAPI spec.
- [Support Teams](https://documentation.ai/solutions/support-teams): Fast, searchable self-service backed by an AI assistant that answers with citations, plus the signals that show which articles are failing.
- [Operations Teams](https://documentation.ai/solutions/operations-teams): SOPs, runbooks, onboarding guides, and internal policies in one searchable place that stays current, so new hires ramp without interrupting anyone.
- [API Documentation](https://documentation.ai/solutions/api-documentation): Import an OpenAPI spec and get a typed reference, generated code samples, and a live try-it console that stays in sync as your API changes.
- [Developer Documentation](https://documentation.ai/solutions/developer-documentation): SDK guides, quickstarts, and tutorials on a docs-as-code workflow, with an MCP server that makes every page readable by AI coding agents.
- [Help Center](https://documentation.ai/solutions/help-center): A fast, searchable help center with an embedded AI assistant that answers in your customers’ words and cites its source, so fewer become tickets.
- [Internal Knowledge Base](https://documentation.ai/solutions/knowledge-base): An internal knowledge base for SOPs, runbooks, and onboarding, with role-based access, AI search, and workflows that flag stale content.
- [Product Documentation](https://documentation.ai/solutions/product-documentation): Feature overviews, onboarding flows, changelogs, and release notes, drafted from your repository so the docs move when the product does.
- [AI-Ready Documentation](https://documentation.ai/solutions/ai-ready-documentation): A hosted MCP server on your docs domain, auto-generated llms.txt and llms-full.txt, and content structured so agents and people read one source.

## Documentation

- [Full documentation index (llms.txt)](https://documentation.ai/docs/llms.txt): Every documentation page, each linked as Markdown. Start here for anything not listed below
- [Documentation home](https://documentation.ai/docs): The product documentation as rendered HTML
- [Introduction](https://documentation.ai/docs/getting-started/introduction.md): What Documentation.AI is and what it is for
- [Core concepts](https://documentation.ai/docs/getting-started/core-concepts.md): The model the product is built on: sites, dimensions, views, and content
- [Quickstart](https://documentation.ai/docs/getting-started/quickstart.md): Create, customize, and publish a first documentation site
- [Web editor](https://documentation.ai/docs/write-and-publish/web-editor.md): Writing and publishing in the browser, with real-time collaboration
- [Code editor](https://documentation.ai/docs/write-and-publish/code-editor.md): Docs-as-code: Git workflows, branches, and MDX in your own editor
- [Components](https://documentation.ai/docs/components/components.md): The full MDX component library available in a page body
- [AI Documentation Agent](https://documentation.ai/docs/ai/ai-documentation-agent.md): The agent that drafts and updates pages against GitHub context
- [AI Assistant](https://documentation.ai/docs/ai/ai-assistant.md): Docs-aware answers with citations, embedded in a published site
- [MCP servers](https://documentation.ai/docs/ai/mcp-servers.md): Reader and Authoring MCP servers, for reading published docs or writing them from an AI client
- [REST API](https://documentation.ai/docs/api-reference/overview.md): Read and update documentation, publish deployments, and pull analytics over HTTP
- [Changelog](https://documentation.ai/docs/changelog.md): Releases, fixes, and improvements by version
- [Roadmap](https://documentation.ai/docs/roadmap.md): What is planned next

## Case studies

- [Datafiniti](https://documentation.ai/customers/datafiniti): With Documentation.AI, the Datafiniti team can now offer Ask AI inside the docs, understand what users are asking, identify documentation gaps, and improve their API and product documentation more regularly with AI
- [Videograph.ai](https://documentation.ai/customers/videograph): Videograph migrated their docs from ReadMe to Documentation.AI. The main goal was to make docs easier to implement and maintain across teams.

## Blog

- [Documentation.AI Blog](https://documentation.ai/blog): Guides, comparisons, and best practices on documentation, knowledge management, and AI-native content workflows.

## Blog: Comparisons

- [Theneo Pricing 2026: Plans, Limits & What Teams Pay](https://documentation.ai/blog/theneo-pricing): Theneo is $120 or $400 a month per workspace, with seats included. See what the endpoint caps, project splits, and unpublished prices really add.
- [Theneo Review 2026: Features, Pricing, Performance & Verdict](https://documentation.ai/blog/theneo-review): Theneo is free for one public project, then $120 per workspace per month. A hands-on review of the editor, Ask AI, analytics, and what teams pay.
- [GitBook Pricing 2026: Plans, Add-ons & What Teams Pay](https://documentation.ai/blog/gitbook-pricing): GitBook is $65 or $249 per site per month plus $12 per user. See what the Assistant allowance, translations, and a second site add to the real bill.
- [GitBook Review 2026: Features, Pricing, Performance & Verdict](https://documentation.ai/blog/gitbook-review): GitBook is $65 or $249 per site per month and the Assistant stops at 500 answers. A hands-on review of the editor, Git Sync, AI, and what teams really pay.
- [Mintlify Pricing 2026: Plans, AI Credits & What Teams Pay](https://documentation.ai/blog/mintlify-pricing): Mintlify Pro is $450/mo for 10,000 AI credits, which covers 400 reader questions at 25 credits each. See what a real team actually pays.
- [Mintlify Review 2026: Features, Pricing, Performance & Verdict](https://documentation.ai/blog/mintlify-review): Mintlify Pro is $450/mo for 10,000 AI credits, or 400 assistant answers at 25 credits. A hands-on review of the editor, agent, playground, and real costs.
- [ReadMe Pricing 2026: Plans, Add-Ons & What Teams Pay](https://documentation.ai/blog/readme-pricing): ReadMe Pro is $250/mo, but Ask AI adds $150 and API logs add $100 more. See the full add-on stack and what a real team pays in 2026.
- [ReadMe vs Documentation.AI: Is API-Only Enough in 2026?](https://documentation.ai/blog/readme-vs-documentation-ai): ReadMe Pro is $250/mo, Ask AI adds $150, and metrics add $100 more. We built the same docs on both and priced what a real team ends up buying.
- [ReadMe Review 2026: Features, Pricing, Performance & Verdict](https://documentation.ai/blog/readme-review): ReadMe is free for one person and $250/month for five. A hands-on review of the API explorer, the AI suite, the seat limits, and what teams actually pay.
- [Best AI Tools for Documentation in 2026 (Compared)](https://documentation.ai/blog/ai-tools-for-documentation): Best AI tools for documentation in 2026 compared by use case. Find the right platform for API documentation, internal knowledge bases, SOPs, and developer docs.
- [Best Developer Documentation Tools in 2026](https://documentation.ai/blog/developer-documentation-tools): See the 7 best developer documentation tools for 2026 for API, code, and internal docs, compared on features, AI support, pricing, and use case.
- [7 Best API Documentation Tools in 2026](https://documentation.ai/blog/api-documentation-tools): 7 API documentation tools compared for 2026 on onboarding, API playgrounds, pricing (from $0), and adoption. See which platform ranks best and why it wins.
- [9 Best Document360 Alternatives for Documentation in 2026](https://documentation.ai/blog/document360-alternatives): Compare the best Document360 alternatives in 2026. See how modern AI documentation platforms differ in workflows, automation, publishing, and pricing.
- [5 Best ReadMe Alternatives for API Documentation in 2026](https://documentation.ai/blog/readme-alternatives): ReadMe Pro is $250/month for five Admins, and Ask AI adds $150. Compare Documentation.AI, Mintlify, Redocly, Fern, and GitBook on roles, AI, and cost.
- [5 Best GitBook Alternatives in 2026: Pricing, AI & Fit](https://documentation.ai/blog/gitbook-alternatives): The 5 best GitBook alternatives in 2026, compared on per-site pricing, reader AI, editing, and migration, from Documentation.AI and Mintlify to Docusaurus.
- [Document360 vs Mintlify: Knowledge Base vs Docs-as-Code (2026)](https://documentation.ai/blog/document360-vs-mintlify): Compare Document360 and Mintlify to see how managed knowledge bases differ from docs-as-code workflows, and which approach fits teams better in 2026.
- [Document360 vs ReadMe: Knowledge Base vs API Docs (2026)](https://documentation.ai/blog/document360-vs-readme): Document360 vs ReadMe in 2026: knowledge base vs API docs. Compare AI, maintenance, and pricing from ReadMe's $250/mo Pro to Document360's quote-based plans.
- [GitBook vs Document360: Docs Tools Compared in 2026](https://documentation.ai/blog/gitbook-vs-document360): Compare GitBook and Document360 through hands-on testing to understand how collaborative documentation and governed knowledge bases differ in 2026.
- [ReadMe vs GitBook: API Docs vs Collaborative Docs (2026)](https://documentation.ai/blog/readme-vs-gitbook): ReadMe vs GitBook detailed comparison in 2026 based on real usage. Explore AI features, editing workflows, publishing, and pricing differences for modern teams
- [Document360 vs Documentation.AI: Features & Cost in 2026](https://documentation.ai/blog/document360-vs-documentation-ai): Document360 vs Documentation.AI. See why teams looking for a Document360 alternative are choosing Documentation.AI for modern documentation workflows in 2026.
- [GitBook vs Documentation.AI: Multi-Site Cost in 2026](https://documentation.ai/blog/gitbook-vs-documentation-ai): GitBook bills $65 or $249 per site per month plus $12 per user. Documentation.AI Pro is $159 flat for four projects. We tested both on setup, AI, and real cost.
- [Mintlify vs GitBook: Detailed Comparison (2026)](https://documentation.ai/blog/mintlify-vs-gitbook): Mintlify vs GitBook: an in-depth, hands-on comparison covering documentation workflows, editing experience, publishing, and team collaboration in 2026.
- [Mintlify vs ReadMe: Detailed Documentation Comparison (2026)](https://documentation.ai/blog/mintlify-vs-readme): Mintlify vs ReadMe (2026): a hands-on comparison of onboarding, editing, AI, publishing, and pricing to help you pick the right documentation platform faster.
- [Mintlify vs Documentation.AI: Features & Credits in 2026](https://documentation.ai/blog/mintlify-vs-documentation-ai): Mintlify vs Documentation.AI compared for 2026: editor scope, AI agents, published docs, and credit pricing. 10,000 credits at $450 vs 30,000 at $159.
- [5 Best Mintlify Alternatives in 2026 (Free & Open Source)](https://documentation.ai/blog/mintlify-alternatives): The 5 best Mintlify alternatives in 2026, free and open-source options included, compared on pricing, AI, and editing, from Documentation.AI to Docusaurus.

## Blog: Guides

- [How to Write a Product Manual: Process, Template and Tools (2026)](https://documentation.ai/blog/how-to-write-a-product-manual): How to write a product manual: a 9-step process, what it must contain, a copyable spec, compliance rules, best practices, and how to choose a tool.
- [How to Write an Instruction Manual for Software: Steps and Template (2026)](https://documentation.ai/blog/how-to-write-an-instruction-manual): How to write an instruction manual for software: prerequisites, steps, expected output, inline error handling, versioning, and a template you can copy.
- [How to Write a User Manual: Template, Steps and Examples (2026)](https://documentation.ai/blog/how-to-write-a-user-manual): How to write a user manual: a free template, a 10-step process, procedure structure, writing rules, standards, and examples for software products.
- [How to Password-Protect Text in 2026: Methods and Best Practices](https://documentation.ai/blog/how-to-protect-text-with-a-password): Learn how to protect text with a password in 2026 and when it’s not enough. Explore access control, authentication, and modern documentation security practices.
- [How to Reduce Support Tickets with AI + Documentation (2026)](https://documentation.ai/blog/reduce-support-tickets-better-documentation-ai): Reduce support tickets with AI-ready documentation. A practical playbook plus the deflection benchmarks (25–65%) and metrics that prove it works.
- [What Is AI Documentation and Why It Matters Today](https://documentation.ai/blog/what-is-ai-documentation): AI documentation keeps product docs accurate and AI-ready. With 90% of leaders saying docs influence buying decisions, see how AI improves quality and speed.
- [Diátaxis Framework: Organize Documentation for Users, Not Authors](https://documentation.ai/blog/diataxis-framework): Learn how the Diátaxis Framework organizes documentation around user intent and helps you create clearer, more structured, and more usable documentation.
- [Importance of Documentation in the AI Era](https://documentation.ai/blog/importance-of-documentation): Why documentation matters more in the age of AI: it drives discovery and onboarding, and it is what AI assistants and MCP read to keep their answers accurate.

## Blog: Engineering

- [How We Give Every Docs Branch Its Own Search Index](https://documentation.ai/blog/docs-branch-search-index): Every Documentation.AI docs branch gets its own turbopuffer search index, a copy-on-write clone ready in about a second, for about three cents.

## Optional

- [Get a demo](https://documentation.ai/get-a-demo): Book a walkthrough with the team
- [Contact](https://documentation.ai/contact): Support, sales, community, and documentation links
- [Community Slack](https://join.slack.com/t/documentationai/shared_invite/zt-3dl0x2qds-L85dnLpKyZ6oc5ZLba9_~Q): Public Slack workspace invite
- [Blog RSS](https://documentation.ai/blog/rss.xml): Feed of every published article
- [Sitemap](https://documentation.ai/sitemap.xml): Every URL on the marketing site, including author pages and category listings
- [Documentation sitemap](https://documentation.ai/docs/sitemap.xml): Every URL in the documentation app
- [Privacy Policy](https://documentation.ai/legal/privacy): How the site and product handle personal data
- [Terms of Service](https://documentation.ai/legal/terms): Terms governing use of the product
- [Subprocessors](https://documentation.ai/legal/subprocessors): Third parties that process customer data