Detector · identity
Person names tokenization
Names are hard to detect reliably from regex alone. Cypherz uses three layers: title patterns (Mr./Mrs./Dr. + Name), salutation context (Dear/Sincerely/Best + Name), and per-project custom dictionaries you can paste in directly. Add your customer list once; every prompt that mentions a customer gets tokenized automatically.
01
Title-anchored detection
Anchored on Mr/Mrs/Ms/Miss/Dr/Prof + capitalized name pattern.
02
Salutation-anchored detection
Dear/Hi/Hello/Sincerely/Regards + name pattern.
03
Custom dictionaries
Paste your customer roster, product names, or internal codewords. Cypherz tokenizes them on sight regardless of context.
04
False-positive resistant
Common place names (New York, San Francisco, etc.) are denylisted to avoid mis-tokenization.
Same input, with and without Cypherz
// Without Cypherz — the model sees real data:
Hi Marcus, please ship the contract to Sasha Petrov.
// With Cypherz — the model sees surrogates:
Hi <NAME_a1b2c3d4e5f6>, please ship the contract to <NAME_d4e5f6a1b2c3>.
// The application gets the original back inside its trust boundary.Common questions
Frequently asked.
Are person names tokens deterministic?
Yes — within a project, the same input always maps to the same surrogate token. This makes joins, dedupe, and analytics keep working on tokenized data without ever decrypting.
Can I disable this detector for a specific project?
Yes — every detector is toggleable per project at creation time and editable from the dashboard.
What if I have a custom format Cypherz doesn't recognize?
Add a custom regex or literal list per project. Cypherz applies your rules after the built-in detectors run.
Are tokenization mappings encrypted at rest?
Yes — AES-256-GCM with envelope encryption. Each project has its own data-encryption key wrapped under the master key.
Get started
Add person names protection to your AI features.
Sign up, create a project, copy your API key. The first request is tokenized in under sixty seconds.
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