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AI agent for data protection officers

Personal Data Processing Inventory Agent

An accurate, current record of personal data processing

ComplianceLegalExecutives and strategy
See how it worksGet access
Personal Data Processing Inventory Agent: what goes in, what the agent does and what you get

What it does

Privacy laws require a record of what personal data is held, where, why and for how long, but these records go stale as systems change. Each quarter this agent scans system inventories and data catalogs and asks each system owner to confirm data types, purposes, retention and sharing. It then checks the answers against the actual data schemas. If a system holds fields the owner did not declare, it asks the owner again and waits for an explanation. It flags missing legal bases, missing retention periods and vendors receiving data without a data processing agreement, and drafts actions with owners. Every data type needs a retention period. The data protection lead approves the updated record. Edge case: a new vendor receives customer data, so the agent checks for a data processing agreement before the record is approved.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueApprovedNo 1 STARTS WHEN Quarterly review 2 USES A TOOL Scan system inventory and data catalog 3 USES A TOOL Ask owners to confirm data types, purposes,retention and sharing 4 USES A TOOL Read actual data schemas for each system 5 CHECKS THE RESULT Do declarations match schemas? If not: ask owner about undeclared fields. Back to step3. 6 DOES Flag missing legal basis, retention and vendoragreements 7 USES A TOOL Draft actions with owners and dates 8 YOU APPROVE Data protection lead approves record 9 RESULT Record updated
Read the steps as a list
  1. Quarterly review
  2. Scan system inventory and data catalog
  3. Ask owners to confirm data types, purposes, retention and sharing
  4. Read actual data schemas for each system
  5. Do declarations match schemas?If not: ask owner about undeclared fields. Back to step 3.
  6. Flag missing legal basis, retention and vendor agreements
  7. Draft actions with owners and dates
  8. Data protection lead approves recordThe agent waits here for your OK.
  9. Record updated

How it decides

It compares owner declarations with schemas and flags gaps.

  • Undeclared fields must be explained
  • Vendors need agreements
  • Retention required for each data type

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Systems in scope
  • Review frequency
  • Register format
  • Owners

What keeps you in control

It always asks you first

  • Record changes
  • Vendor actions

Hard limits

  • Does not copy personal data
  • Not legal advice

It stops when

  • Done: record updated
  • Stop: legal question

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensIn the Q2 review, the CRM owner declared name and email, but the schema also held date of birth, so the check failed. The agent asked again, and the owner confirmed it was used for age checks. The agent added a legal basis and a two-year retention period. It also found a new survey vendor with no signed agreement. The data protection lead approved both actions.

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