DocsTrust
Commercial guide

Audit Confluence for wrong-answer risk.

Turning on AI does not repair a knowledge base. It makes more of that knowledge retrievable. The audit therefore starts with one high-impact Confluence space, inventories its current pages, prioritizes content risks, and gives administrators a reviewable path from finding to Jira cleanup ticket.

Short answer: A useful Confluence AI readiness audit checks which pages are likely to mislead Rovo, AI Search, support agents, or employees, shows evidence for each finding, and assigns explicit cleanup work. DocsTrust does this without automatic Confluence edits or persistence of full page bodies.

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What the audit should answer

A readiness score alone is not enough. An administrator needs to know which page is risky, what evidence supports the finding, why the risk matters for retrieval, and what a human owner should do next.

DocsTrust separates broad page inventory from bounded AI review. Every loadable current page in the selected scope is inventoried, while configurable AI budgets focus semantic analysis on the most relevant candidates.

  • Which guidance is stale, outdated, deprecated, duplicated, or contradictory?
  • Which pages have no clear owner or contain prompt-injection-like instructions?
  • Which findings are high enough risk to become Jira cleanup work?
  • Which evidence and limitations must a reviewer see before acting?

The four-step workflow

Choose one critical space first: Support, Customer Success, IT, Security, or Sales Enablement are common starting points. Run the bounded audit, review evidence-backed findings, and create Jira tickets only for approved cleanup work.

The V1 product does not edit or delete Confluence pages. This keeps the audit reversible and places the final content decision with the customer.

  • Select a clearly owned space and define the AI use case.
  • Inventory the selected scope and run deterministic plus bounded AI analysis.
  • Triage severity, confidence, rationale, and short evidence snippets.
  • Create explicit Jira cleanup tickets and re-scan after remediation.

Security and data boundaries

DocsTrust is built as an Atlassian Forge app. The V1 posture uses Forge LLMs and declares no external runtime egress. Full Confluence page bodies are processed transiently during a scan and are not persisted in the audit result.

The stored result is intentionally limited to metadata, fingerprints, findings, confidence, short evidence snippets, suggested actions, audit events, Jira links, and settings. These boundaries reduce procurement friction, but they do not replace a customer's own security or legal review.

  • No automatic Confluence edits.
  • No full page-body persistence in the V1 result.
  • Schema-validated AI output and bounded token/page budgets.
  • Human review before Jira cleanup work is created.

Start with one space

Audit one space.

Tell us which space you would start with and whether the target workflow is Rovo, AI Search, support automation, or another internal assistant.

Book a 20-minute audit review