The Challenge
Research institutions face tensions between data sharing and privacy:
- Research ethics require participant privacy protection
- Collaboration requires data sharing across institutions
- Longitudinal studies need consistent pseudonyms
- Publications must not contain identifiable information
The Solution
Consistent, reproducible pseudonymization for research data.
Reproducible
Process the same data again and get identical results.
Research Formats
CSV, JSON, and structured data support for common research formats.
Consistent IDs
Same pseudonym for same identifier across documents. Perfect for longitudinal studies.
Safe Sharing
Share datasets with collaborators without risking participant privacy.
Frequently Asked Questions
How does cloak.business help researchers share datasets safely?
cloak.business provides consistent pseudonymization — the same participant identifier always maps to the same pseudonym across documents and datasets. This preserves data linkage for longitudinal studies while fully protecting participant privacy.
Does cloak.business support IRB and ethics committee de-identification requirements?
Yes. cloak.business detects and removes direct and quasi-identifiers across 320+ entity types. The Replace and Redact methods produce de-identified datasets suitable for IRB-approved sharing and publication under most institutional ethics frameworks.
What research data formats does cloak.business support?
cloak.business supports CSV, JSON, and plain text via the structured data API, plus free-text analysis via the standard text endpoints. This covers common research formats including survey exports, interview transcripts, and clinical data dumps.
Is This Right for You?
Best For
- Organizations with compliance obligations (GDPR, HIPAA, CCPA, PCI-DSS)
- Teams regularly sharing datasets containing names, IDs, or medical records
- Developers building AI pipelines that process user-submitted content
- Enterprises requiring audit logs and reproducible anonymization for legal holds
Not Ideal For
- Single-language English-only pipelines with no PII — regex-only tools may suffice
- Real-time streaming at sub-5ms latency — NLP inference adds overhead
- Fully air-gapped environments without internet access — use Desktop App instead
- Unstructured media files (audio, video) — text extraction is a prerequisite limitation