Block 1 - Document Upload Webhook
- Type / Role
- n8n-nodes-base.webhook - webhook
- Config choices
- Version 2.1
Overview This workflow enables GDPR compliant document processing by detecting, masking, and securely handling personally identifiable information (PII) before AI analysis. It ensures that sensitiv...
n8n-nodes-base.webhook, n8n-nodes-base.set, n8n-nodes-base.code, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmchatanthropic, @n8n/n8n-nodes-langchain.outputparserstructured, n8n-nodes-base.merge, n8n-nodes-base.postgres
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by ResilNext.
Original n8n.io sourceThis workflow enables GDPR-compliant document processing by detecting, masking, and securely handling personally identifiable information (PII) before AI analysis.
It ensures that sensitive data is never exposed to AI systems by replacing it with tokens, while still allowing controlled re-injection of original values when permitted. The workflow also maintains full audit logs for compliance and traceability.
Document Upload & Configuration Receives documents via webhook and initializes configuration such as document ID, thresholds, and database tables.
Text Extraction Extracts raw text from uploaded documents for processing.
Multi-Detector PII Detection Detects emails, phone numbers, ID numbers, and addresses using regex and AI-based detection.
PII Aggregation & Conflict Resolution Merges detections, resolves overlaps, removes duplicates, and builds a unified PII map.
Tokenization & Vault Storage Replaces sensitive data with secure tokens and stores original values in a database vault.
Masking & Validation Generates masked text and verifies that all PII has been successfully removed before AI processing.
AI Processing (Masked Data) Processes the document using AI while preserving tokens to prevent exposure of sensitive information.
Re-Injection Controller Determines which fields are allowed to restore original PII based on permissions.
Secure Retrieval & Restoration Retrieves original values from the vault and restores them only where permitted.
Audit Logging Stores metadata, detected PII types, and re-injection events for compliance tracking.
Error Handling & Alerts Blocks processing and triggers alerts if masking fails or compliance rules are violated.
This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.
Showing the first 24 of 37 workflow blocks. Download the JSON for the full node graph.
| Workflow | Detect and mask PII for GDPR-safe AI document analysis with Anthropic and PostgreSQL |
|---|---|
| Complexity | advanced |
| Nodes | 37 |
| Categories | Document Extraction, AI Summarization |
| Author | ResilNext |
| Published | 25 Mar 2026 |
Use the JSON export at /data/workflows/14320/14320.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.
Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.
Overview This workflow enables GDPR compliant document processing by detecting, masking, and securely handling personally identifiable information (PII) before AI analysis. It ensures that sensitiv...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Document Extraction, AI Summarization use case.