EU AI Act Compliance Cockpit – Prove Your Obligations, Automatically
Automate the EU AI Act and GDPR obligations themselves: a central AI registry, an immutable audit trail, a human-in-the-loop gate for automated decisions, and automatic Article 50 transparency notices. Deadline-safe instead of a spreadsheet.
Real talk: nobody enjoys maintaining compliance documentation. It's one of those tasks that exists because a regulation demands it — not because anyone finds it fun.
Then an authority asks: which AI are you actually using, in which workflow, with what data flow? Who approved that automated rejection? Show me the log. In most mid-sized companies, what follows is a frantic scramble across Make scenarios, n8n workflows, and three different people's heads.
The Hamburg case — a €492,000 fine in September 2025 — shows where that leads: an algorithmic rejection nobody could explain.
The obligations are rule-based, recurring, and documentation-heavy. Which is exactly what automates well. Here's the pipeline.
Before vs. After
| Aspekt | Before | After |
|---|---|---|
| Overview of AI in use | A spreadsheet nobody updates | Self-updating AI registry |
| Automated rejections | Pass through unchecked | Human-in-the-loop gate + log |
| Explaining a decision | Nobody can state the reasons | Audit-trail entry in seconds |
| Article 50 transparency notice | Forgotten or hand-maintained | Injected automatically |
| DPIA / FRIA | Copy-paste from old documents | Template draft, DPO signs off |
| Responding to an authority request | Days of scrambling | One-click export from the registry |
The Challenge
The EU AI Act explicitly binds users of AI, not just developers — run Make, n8n, or Zapier with AI steps and you're a deployer under the regulation. The obligations run in parallel with GDPR and stack: Art. 4 (AI literacy, since February 2025), Art. 50 (transparency, from 2 August 2026), Art. 22 GDPR (no solely automated decision with significant effect without human review — regardless of company size), and Art. 86 AI Act (right to explanation, from August 2026).
In practice, no mid-sized company fully knows which AI building blocks run where, who approved which automated decision, or can explain a single rejection in an understandable way. The AI steps hide across dozens of scenarios on multiple platforms, the only "registry" is a spreadsheet nobody updates, and audit trails exist — if at all — as scattered log lines with no context.
Regulators are already acting, even before the high-risk obligations bite: Hamburg's Data Protection Commissioner imposed €492,000 primarily for breached information and transparency obligations on an algorithmic rejection. A company with nothing to show rebuilds that same case in its own house — and, in the worst case, pays an AI Act fine and a GDPR fine side by side.
Our Solution
A central compliance cockpit built as an n8n workflow, self-hosted for full data sovereignty. An automatic scan detects AI steps across all connected platforms (Make, n8n, Zapier) and writes them into a living AI registry: which workflow uses which model, with what data flow, in which AI Act risk class. Instead of a dead spreadsheet, you get a record that keeps itself current.
Automated decisions with legal or significant effect — rejections, creditworthiness, applications — don't just pass through; they enter an approval queue. The human decides, the workflow documents. Every AI step writes an immutable audit log with input, model, output, timestamp, and human override. The explainability the Hamburg company failed on becomes a database row instead of a crisis.
Public-facing AI automatically gets the Article 50 transparency notice injected — chatbot labelling, AI-content marking, deepfake disclosure. For affected systems, an AI-assisted template produces DPIA and FRIA drafts with reusable, overlapping content; final sign-off stays with the data protection officer. An honest caveat: the cockpit doesn't replace legal advice. It makes compliance demonstrable, deadline-safe, and auditable — a human still sets the legal frame.
Key Features
Automatic AI Registry
A scan detects AI steps across Make, n8n, and Zapier and auto-maintains a central record: which workflow uses which model, with what data flow, in which AI Act risk class. Instead of a spreadsheet nobody keeps current.
Audit Trail by Design
Every AI step writes an immutable log — input, model, output, timestamp, human override. The explainability the Hamburg company failed on becomes a database row instead of a crisis.
Human-in-the-Loop Gate
Automated decisions with legal or significant effect (rejections, creditworthiness, applications) enter an approval queue. The human decides, the workflow documents — compliant with Art. 22 GDPR and Art. 14 AI Act.
Automatic Article 50 Notices
Chatbots, AI content, and synthetic media get the transparency notice injected automatically — the next hard deadline (2 August 2026) becomes a configured default instead of manual upkeep.
DPIA & FRIA Drafts from Templates
For affected systems, a template produces DPIA (Art. 35 GDPR) and FRIA (Art. 27 AI Act) drafts with reusable, overlapping content. The FRIA doesn't replace the DPIA — both stay auditable, the DPO signs off.
Deadline & Status Dashboard
A cockpit shows open obligations, upcoming deadlines (Art. 50, NIS2 registration, CRA), and the compliance status per AI system — so no deadline gets buried in an inbox.
Results
Possible setup, not a packaged product
The figures shown are target values and expected magnitudes for a possible setup – based on industry benchmarks, public studies of comparable setups, and our own tests on a real stack. They are not measured outcomes from a specific customer project; actual results depend on company size, process maturity, and integration depth. We do not offer this setup as a packaged product. We help teams design, automate, and run such processes themselves – through architecture consulting, workshops, and implementation support with n8n. For regulated third-party systems with certification or license requirements (e.g. HIS, gematik, DATEV-certified), we partner with specialized providers.
Scattered AI steps become a demonstrable, deadline-safe registry — every automated decision explainable, Article 50 notices automatic, DPIA/FRIA as a draft instead of copy-paste
Integrations
Seamless connection to your existing infrastructure
n8n (self-hosted)
OrchestrationCentral workflow engine: scan, registry, audit trail, approval gates, and dashboard
Make / Zapier
AI InventoryScanned via webhook/API to pull hidden AI steps into the registry
PostgreSQL
Audit LogImmutable record of all AI steps and approvals, archivable in an audit-proof way
Claude / GPT (EU endpoint)
Document DraftingGenerates DPIA/FRIA drafts and explanation texts via DPA-compliant EU endpoints
Slack / Microsoft Teams
Approval WorkflowHuman-in-the-loop notifications with one-click sign-off for the DPO and business owners
S3-compatible storage
ArchivingAudit-proof storage of DPIA/FRIA, logs, and transparency evidence
Security & Compliance
Enterprise-ready with highest security standards
Data Sovereignty via Self-Hosting
The entire workflow runs self-hosted (n8n) in your own data center or EU hosting. Sensitive compliance metadata never leaves the house — no data flowing to external clouds.
Immutable Audit Trail
Every AI step and every approval is logged tamper-evident with timestamp, actor, and content. Auditable toward regulators, defensible in later disputes.
GDPR & AI Act Considered in Parallel
Human-in-the-loop (Art. 22 GDPR / Art. 14 AI Act), transparency (Art. 50), explainability (Art. 86), and DPIA/FRIA are built as separate, combinable blocks — because compliance with one regime doesn't satisfy the other.
EU Endpoints for AI Calls
Model calls run either via local open-source models or DPA-compliant EU endpoints of commercial LLMs — matched to the data protection level of each use case.
Technology Stack
Frequently Asked Questions
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