Document Testing for the AI Age
AI agents simulate employees completing tasks using your documentation. If the agent succeeds, your docs pass. If it fails, you know exactly what to fix.
Pre-seed stage · Enterprise customers · Revenue generating
Documents are task-completion resources
- ●At their core, documents exist for one purpose: to help people complete tasks.
- ●An API doc helps developers integrate.
- ●A policy doc helps employees make decisions.
- ●A runbook helps ops teams respond to incidents.
The question is: can someone actually complete the task using these docs?
Sit a real person at a desk and have them try
The perfect way to test documentation is simple: put a smart person at a workstation, give them only your docs, and ask them to complete the task. If they succeed, your docs work. If they fail, you know exactly where the gaps are.
This is the gold standard. But there's a problem...
Smart people are expensive and scarce
A single documentation test can take an engineer hours. Testing a full docs suite means days of work.
At $150/hr, testing 50 docs costs $7,500+. Every time you update docs, you need to test again.
Enterprise companies have thousands of documents. Manual testing doesn't scale.
Different testers have different backgrounds. Results vary based on who's testing.
So companies either don't test docs at all, or they use unreliable proxies like page views and word counts.
AI agents simulate employees completing tasks
We give an AI agent the same setup a real employee would have: your documentation, a task to complete, and the tools they'd use. The agent attempts the task using only what's in your docs.
The agent works through the task exactly like a new hire would.
If it succeeds, your docs work. If it fails, we show you exactly where.
Four steps to validated documentation
Write a test
Define what task you want the AI to complete and what success looks like.
AI attempts the task
An AI agent reads your docs and tries to complete the task using only that information.
Judge evaluates
A separate AI judge reviews the result against your success criteria. Unbiased, consistent.
Pass or Fail
Get a clear verdict with detailed reasoning. Know exactly what's working and what needs fixing.
As AI improves, Dokumen improves automatically
Unlike products that compete with AI, Dokumen rides the AI wave. Every improvement in language models makes our tests more accurate, faster, and cheaper to run.
Smarter
Better models understand nuance better. Tests catch more subtle documentation gaps.
Faster
Inference speed keeps improving. Tests that take minutes today will take seconds.
Cheaper
Token costs drop 10x every 18 months. Our margins improve automatically.
The Moat Deepens Over Time
Every customer test run generates data on documentation patterns. We use this to improve test design and recommendations. The more tests run on our platform, the better we get at catching documentation issues.
Let's talk about the future of documentation testing
We're at pre-seed stage with paying enterprise customers and a clear path to scale. We'd love to share our vision and traction with you.