π’ Typical use cases
Textwash Pro is built to support real-world anonymisation workflows in research, industry, and the public sector.
If your use case involves unstructured text and personal data, Textwash Pro is likely relevant.
Not sure? Reach out at
textwash-pro@jocapps.eu
π‘οΈ
GDPR-compliant data anonymisation
Anonymise free-text fields that contain personal data before storing or sharing them:
- Customer support logs and email archives
- Contact forms and CRM notes
- Internal reports with narrative descriptions
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Archiving & records retention
Keep long-term text repositories usable while reducing privacy risk before archival storage:
- Legacy case files and historical correspondence
- Retention-ready email and document collections
- Internal knowledge bases with personal references
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Open Science & data sharing
Prepare research datasets for sharing while protecting participantsβ identities:
- Survey open-ended responses
- Interview and focus group transcripts
- Field notes and qualitative research data
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Legal, Health, & Social services
Remove direct and indirect identifiers from sensitive case descriptions:
- Clinical notes and case vignettes
- Legal case summaries and memos
- Social work documentation and protocols
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User research & UX feedback
Anonymise qualitative feedback before sharing within teams or with external partners:
- User interviews and usability tests
- App store reviews and support tickets
- Internal product discovery notes
π
Logs & monitoring data
Remove PII from semi-structured logs before central storage or analysis:
- Application and server logs containing user details
- Chat logs from support systems
- Exported audit trails and monitoring outputs
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Proxy & preprocessing for LLM workflows
Route prompts and free-text inputs through anonymisation before they reach external or internal LLM systems:
- PII-safe prompt proxy for shared AI assistants
- Preprocess support tickets before summarisation
- Mask identifiers prior to retrieval, ranking, and generation
ποΈ Custom institutional workflows
We design end-to-end anonymisation workflows that align with institutional governance, legal obligations, and research quality standards.
π Governance alignment
Policy mapping, retention definitions, and approval checkpoints for every data flow stage
π‘οΈ Controlled processing
Role-based access setup, secure review loops, and privacy controls for internal and external teams
π Audit readiness
Documented procedures, quality evidence, and repeatable validation protocols for compliance reviews
For institutional rollouts, integration planning, or compliance questions, contact
textwash-pro@jocapps.eu