Today, writers manually scan PRs in tools like Cursor, identify what needs updating, build a plan, and draft from scratch. The Content Writer Agent automates the detection and drafting layers. It monitors merged PRs and changelogs, identifies every affected article, and delivers drafts with cited sources through your existing PR workflow. What used to be a multi-day scramble becomes a managed queue.
For Documentation Leaders
Turn your docs into an answer engine.
Your docs are the highest-leverage asset you own. When they fall behind, every team feels it: support, onboarding, even AI answers. Inkeep closes the gap between what your team knows and what your docs say.
Trusted by leading teams
The moment
Someone just landed in your docs.
They have a question, and about 30 seconds of patience. Those 30 seconds decide whether they find the answer or give up on your docs.
docs.yourcompany.com
How do I configure SSO for my workspace?
00:30 to find it
The problem
Users fail to find answers for two reasons.
The answer exists, but users can't find it
Keyword search returns pages, not answers. Users scroll through nav trees, scan headings, and give up. The content is there. The discoverability isn't.
- Prospects leave before they see what you offer
- Customers file tickets for answers already in the docs
- Support volume increases with questions the docs should answer
The answer doesn't exist yet
A product ships, but the docs never get updated. Signals are scattered across Slack, GitHub, and your ticketing system. Nobody owns the gap.
- Users hit dead ends and lose trust
- Support answers the same question repeatedly
- Your docs fall further behind with every release
The cost
Where it shows up
Impacts to the business
Ticket deflection rate: fewer questions get resolved before reaching support
Average handling time: agents spend longer researching answers that should be in the docs
Prospect churn: prospects leave your site without finding what they need
Impacts to the docs team
Docs coverage: you know there are gaps, but no easy way to find or prioritize them
Docs freshness: content drifts as product ships
Time-to-publish: drafting from blank takes hours
The fix
Inkeep turns your docs into an answer engine.
AI-native answers across docs, support, and your product, built on the content you already have.
Summary
What changes with Inkeep.
Without Inkeep
Users search your docs and leave empty-handed
Docs fall behind with every product release
Support answers questions your docs should cover
Prospects bounce before finding what they need
Writers spend hours drafting from scratch
With Inkeep
Users get cited answers in seconds
Docs get updated automatically from tickets and PRs
Support volume drops as users self-serve
Prospects find answers and convert
Writers review drafts, not blank pages
I will never use a tool that just allows people to introduce garbage into my system... AI is amazing. However, even Inkeep I want a human in the loop.
Casey Smith, Head of Documentation, Payabli
Read more
Inkeep provides feedback loops to improve our docs and identifying the gaps was probably the biggest thing we were able to solve.
Alvin Ciby, Director of Growth, Fingerprint
Read moreExplore other use cases
Frequently asked questions
It consolidates signal sources that today are scattered: search misses from your AI assistant, closed support tickets, Discord and Slack questions, merged code changes, and patterns in real user conversations. These converge into a single prioritized queue so your team works on what matters most, not what's loudest. The weekly gap report stops being a backlog and starts being actionable.
No. It removes the upstream load. Detection, triage, and drafting from a blank page crowd out the higher-leverage work that only experienced writers can do: editing for voice, sharpening structure, deciding what not to publish. The agent absorbs the detection and drafting layers. Writers review and refine instead of starting from scratch.
Keyword search returns pages. People need answers. The gap between the two is where users bounce. A prospect tries a competitor and never returns. A customer opens a ticket and waits. Inkeep's AI Search understands intent and returns a direct, cited answer in seconds. It's not a funnel problem or a support problem. It starts as a docs gap, one you can see and close.
Yes. Inkeep integrates with Docusaurus, GitBook, ReadMe, Mintlify, Confluence, custom-built sites, and more. Content updates route through GitHub PRs regardless of your publishing stack. The AI Search component embeds directly on your docs site. No migration required.
A 4-week pilot on your existing docs, with your team in the loop. A forward-deployed engineer co-builds alongside your team, not a self-serve checklist. You bring your three 'happy path' questions: the conversations you most want to demo well. We build toward those. Target 10-20 drafted articles over the pilot window, with weekly check-ins and a mid-pilot scorecard.
A significant share of your docs traffic now comes from LLM agents crawling content on behalf of users. Content that's incomplete, stale, or inconsistent in structure fails both audiences. Humans get bad answers, and AI agents pull bad context downstream. When your docs are comprehensive and current, AI agents cite you instead of your competitor's. This makes docs a top-of-funnel pipeline asset, not just a customer retention tool.
