Data Preparation
GDPR-Compliant Data Anonymization
Automatic removal of personally identifiable information with AI for GDPR-compliant text analysis
GDPR anonymization from deepsight cloud detects and removes names, email addresses, phone numbers, and other personal data from free texts – automatically and context-preserving for valid analyses.
GDPR-Compliant Data Anonymization im Workflow
Fügen Sie das Anonymisierungs-Modul per Drag & Drop in Ihren Workflow ein
The Challenge
The Challenge
GDPR and data protection laws require protecting personal data in text analysis. Manual anonymization is time-consuming, error-prone, and costly. A single mistake can lead to serious data breaches.
GDPR violations with high fines
Data protection issues and loss of trust
Legal consequences and liability risks
Die Lösung
Intelligent Anonymization
Our AI automatically detects and removes personal data while preserving context and analyzability:
Automatic Detection
AI detects names, emails, phone numbers automatically
GDPR-Compliant
100% compliant with Art. 25 & 32 GDPR
Context-Preserving
Texts remain analyzable and semantically meaningful
Flexible Methods
Redaction, pseudonymization, or generalization
Anwendungsfälle
Use Cases
Where anonymization is used
Anonymize HR Feedback
Analyze employee feedback GDPR-compliant without personal data
- Mask names and departments
- Remove salary data
- Preserve context for analysis
Market Research Data
Anonymize survey data for external analysis
- Remove contact information
- Mask company names
- Enable external analysis
Compliance & Audits
Ensure GDPR compliance
- Automatic checks
- Generate audit trail
- Ensure legal certainty
FAQ
Frequently Asked Questions
Our AI detects names, email addresses, phone numbers, postal addresses, IP addresses, account IDs, and other personal data based on context and pattern recognition.
Yes, anonymization meets GDPR requirements (Art. 25 & 32). On-premise deployment available for maximum data control.
AI-powered detection achieves >95% accuracy. Regex-based detection for structured data (emails, phone numbers) is nearly 100% precise.
Yes! Pseudonymization and generalization preserve context and semantics. Only direct identifiers are replaced.
In the Enterprise plan, you can add custom regex patterns and industry-specific PII definitions.
More Modules
Discover Related Modules
Combine modules for a complete analysis workflow