For Privacy & Compliance

Production-shaped data. PII-safe by default.

Mark fields as sensitive in your DataMaker template and the agent guarantees they're masked, replaced, or never exported. GDPR-friendly. Audit-ready.

Why masking is hard

Brittle anonymisation slows everything down.

Hand-rolled scripts drift

Every team writes its own anonymiser. They miss new PII fields, fail audits, and break with each schema change.

Production copies are a liability

A snapshot of prod for testing is a GDPR incident waiting to happen — even with a 'safe' subset.

Synthetic data is too unrealistic

Faker gives you 'John Doe' rows that don't trigger the bugs real customers hit. Tests pass; production doesn't.

How DataMaker protects PII

Masked at the field. Tracked at the schema.

Sensitive fields are first-class. Templates declare them; the agent honours them.

Sensitive flag

Mark any field sensitive

Add a flag in the template. Exports are blocked unless explicitly approved, and the agent refuses to copy the value.

Locale-correct fakes

Realistic without being real

Generate IBANs that pass checksum, USt-IDs that match country format, addresses that match postcodes.

Format-preserving

Same shape, different identity

Email "alice@…" → "fcbb@…". UUIDs stay UUIDs. Dates stay dates. Tests behave the same way.

Agent-aware

Refuses unsafe exports

The AI agent will not copy sensitive fields out of templates without explicit instruction — by design.

Template with sensitive fields

Mark a field. Generation is masked.

DataMaker substitutes a realistic, locale-correct fake at generation time and refuses to export the underlying value.

  • GDPR-compliant by default
  • Mask, replace, or block-on-export
  • Audit log per template
  • Locale-aware substitutions
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Our DPO signed off our DataMaker rollout in a single review. The sensitive-flag at the template level was the clincher.

VP Engineering, EU healthtech

Realistic test data without the GDPR risk.

Try the masking workflow on the free tier — no production data needed.