AI Documentation Reliability Platform

Your Product Changed. Did Your Documentation?

BookPetal links code, product facts, and documentation — then detects drift, maps impact, and generates reviewable patches backed by source evidence.

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Click a pipeline step below to walk through the workflow — no scrolling required.

Detect · Scanning documentationAPI Reference · Create Organization

The core problem

Products Change Faster Than Documentation

Manual maintenance by PMs, engineers, and technical writers cannot keep pace with continuous product iteration.

  • API fields updated — docs still show old parameters
  • Page entry points changed — help articles use outdated paths
  • New permissions live — guides omit required roles
  • Interfaces deprecated — code examples still call them
  • Releases ship without migration guides or FAQs
  • Same feature named differently across pages
  • Support teams answer questions docs should cover
  • Engineers cannot see which docs a code change affects

Product Truth Index

Specific Intelligence — Not Vague Alerts

BookPetal links facts in code, APIs, releases, and tasks to the paragraphs and examples they support.

Which paragraph

needs modification

Why

with cited product basis

What else

pages are simultaneously affected

Suggested content

with version scope

Who reviews

writers, PMs, engineers

Verification

safe merge to doc repo

Automatic detection

What BookPetal Identifies On Every Change

When code, APIs, permissions, pricing, or workflows change, the platform surfaces actionable drift — not generic warnings.

Outdated documentation pagesInconsistent paragraphs Deprecated API parameters in examplesMissing prerequisite steps Undocumented new featuresMissing migration guides & FAQs AI answers without reliable sources

BookPetal is not

  • A documentation CMS
  • A generic AI writing tool
  • A traditional knowledge base
  • A simple docs Q&A chatbot

Built for

Documentation That Evolves With The Product

AI Documentation Infrastructure for API companies, developer tools, B2B SaaS, and AI startups — not traditional publishing.

API companiesDeveloper toolsB2B SaaSAI startups

Keep Every Document True · One product change unfolds across API docs, help centers, migration guides, release notes, and support briefs.

Why continuous AI

High-Frequency Analysis At Product Scale

Every PR merge, OpenAPI update, version tag, or task completion re-triggers indexing, impact mapping, scanning, patch generation, QA, and Q&A updates.

  1. Understand product materials — commits, schemas, tasks, release notes, help docs, support data
  2. Semantic comparison — detect drift beyond keyword changes (e.g. workspace admin → organization access)
  3. Generate fix content — API Reference, Quick Start, Migration, Changelog, FAQ, support briefs
  4. Run document QA — facts, steps, versions, terminology, code, links, permissions after every change
  5. Grounded Q&A — answers with version scope and sources; conflicts prompt human confirmation
  6. Re-analyze every release — full cycle on each product event