THE PRIVACY BOUNDARY
Send useful data to AI without sending the identity with it.
Pseudonymize names, emails, locations and other identifiers before prompts, files and structured payloads reach LLM providers or other external systems.
"Summarize support history for Alice Rossi.
[email protected] has disputed invoice INV-204."
"Summarize support history for PERSON_01.
EMAIL_01 has disputed invoice INV-204."
Built for the boundary between your data and external systems.
Predictable transformations, not black-box masking.
Control how identifiers are detected, replaced and kept consistent across your data.
Preserve identity relationships
The same identifier can map to the same pseudonym within a defined scope, so downstream systems keep useful relationships without receiving the original value.
Alice requested a refund
PERSON_01 requested a refund
Keep structured payloads usable
Transform values without flattening JSON, message arrays or application-specific structures.
"user": {
"name": "PERSON_01",
"email": "EMAIL_01"
},
"ticket_id": "TK-4821"
}
Choose what gets transformed
Configure entity types and transformation behavior instead of applying one irreversible redaction rule to everything.
"entities": [
"person",
"email",
"phone",
"iban"
]
}
Hosted API or open-source engine
Integrate the managed API for zero overhead, or run the engine locally when data must remain inside your environment.
Redaction removes context. Pseudonymization preserves relationships.
Original
Redaction
Pseudonymization
Inspect the handling, not the adjectives.
- Latency
- 37 ms median latency for 10 KB text payloads.
- Telemetry
- Request and response bodies are never written to logs.
- Region
- Hetzner EU (Falkenstein)