practical guide targeting compliance and legal operations teams.
The Challenge
Every organization has internal identifiers that are personally identifiable in context but don't match standard PII patterns: employee IDs, customer account numbers, internal reference codes, proprietary patient identifiers, order numbers linked to individuals. Standard PII tools (including Presidio's base configuration) detect universal identifiers like SSNs and email addresses but cannot know about organization-specific formats. Internal identifiers left in shared documents, support tickets, or data exports can re-identify individuals when combined with other data — a GDPR pseudonymization failure.
By the Numbers
- Internal identifiers left in shared documents, support tickets, or data exports can re-identify individuals when combined with other data — a GDPR pseudonymization failure.
Real-World Scenario
A financial services firm has customer account numbers in the format "ACC-XXXXXXXX-XX" that appear throughout support ticket exports. Standard PII tools miss them entirely. Using anonym.legal's custom entity builder, their compliance team creates a pattern in 10 minutes. All 180,000 historical support tickets processed in batch now have account numbers redacted alongside standard PII. Re-identification risk eliminated without an engineering ticket.
Technical Approach
Custom entity creation with AI-assisted pattern generation. Users describe their identifier format in plain language ("Employee IDs that start with EMP followed by 5 digits") and the AI generates the appropriate regex pattern. Custom entities integrate seamlessly with the existing 260+ type detection. Results can be saved as presets and shared across teams. Zero engineering required — compliance and legal teams can define their own patterns.
Comments (0)