entity Data Context

Zero-Trust PII
Entity Protection.

Precisely target and anonymize specific entities: Names, Locations, Social Security Numbers, Credit Cards, and API Keys. Maintain full AI syntax support.

Systematic Privacy Risks

Regex Engine Timeouts

Complex nested PII matching often crashes cloud servers. Local processing uses your own hardware capability limitlessly.

Custom Entity Misses

Standard DLP tools miss proprietary internal tracking IDs or unique medical formats completely.

Numeric Context Loss

Failing to differentiate a medical ID from a dosage amount destroys the medical logic for the AI.

Vector DB Sync: Raw Data Upload

Vector DB Sync: Tokenized [NAME_1] Object

100% LOCAL BROWSER INJECTION

Zero-Trust Operational Flow

Offline compliance methodologies for scalable data

01

Offline Staging

Load formats natively into edge memory.

02

Regex Enforcement

Execute deterministic entity detection locally.

03

Clean API Call

Safely interact with external models post-masking.

04

Key Reconstruction

De-tokenize dynamically returning context.

Regulatory Trust Framework

PCI-DSS

Satisfied

Mask credit card numbers locally

HIPAA

Satisfied

Protect 18 PHI identifiers

FERPA

Satisfied

Secure student ID digits

GDPR

Satisfied

EU national identity numbers

ENTITY Intelligence Deep-Dive

Can I add my own custom entities to find?
Yes. PrivacyScrubber PRO allows you to add Custom Regex rules to detect and mask proprietary formats like AWS Keys or Patient UUIDs.
How accurate is the Name detection?
Our Name tagger focuses on capitalized contiguous nouns in contextual English sentences. Unsure data can always be verified manually via the UI.
Does it detect international phone numbers?
Yes, our regex heuristics target various formatted global telephony systems, masking them safely into [PHONE_1] tokens.

Ready to Defend Your IP?

Stop relying on APIs. Encrypt entities directly at the edge.

DEPLOY PRO — $9.99 ONE-TIME