DOCUMENT OPS

Auditor Request Evidence Fulfiller

An agent that takes an auditor's plain-English evidence request via webhook, locates the matching artifacts across Confluence and Google Drive, assembles a labeled response bundle.

CategoryDocument Ops
Enginepaperclip
Difficultyadvanced
Triggerwebhook
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWebhook receives auditor request textHTTP webhook
  • LogicAgent parses request into control topics
  • ActionSearch Confluence for matching policiesConfluenceConfluence
  • ActionSearch Google Drive for supporting artifactsGoogle DriveGoogle Drive
  • OutputDeliver labeled bundle to shared DropboxDropboxDropbox

What it does

Handles ad-hoc auditor requests in natural language. An auditor asks for, say, 'Q1 access review approvals and the change-management policy,' and the agent interprets the ask, finds the right documents wherever they live, and returns a tidy, labeled bundle, instead of an analyst playing fetch over email.

When to use it

Use it during active fieldwork when auditors send a steady stream of one-off evidence requests and you want consistent, fast, fully-sourced responses without a human triaging each one.

How it works

  1. 1An inbound webhook delivers the auditor's request text and a request ID.
  2. 2The agent parses the request into specific control topics and document types.
  3. 3It searches Confluence for matching policies and procedures.
  4. 4It searches Google Drive for the supporting operational artifacts.
  5. 5It reasons over the results, labels each file with the control it satisfies, and notes anything it couldn't find.
  6. 6It delivers the assembled, indexed response bundle to the shared Dropbox request folder.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect ConfluenceSpaces, pages, blueprints.
  3. 3
    Connect Google DriveDocs, sheets, slides, files.
  4. 4
    Connect DropboxFiles and folders.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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