PII Catalog Proof of Concept

The database was clean until the audit script flagged three fields glowing red: full names, email addresses, and birth dates. Sensitive. Traceable. PII. That moment is why teams build a PII Catalog Proof of Concept.

A PII Catalog Proof of Concept is a focused build that scans data sources, detects personally identifiable information, and maps it into a searchable index. It proves that your detection logic works before you commit to a full production rollout. Engineers use automated discovery against structured and unstructured data, parsing tables, logs, and object storage for fields that match patterns or exceed confidence thresholds.

The catalog acts as the single source of truth for where PII lives inside your systems. It records metadata: source location, data type, sensitivity score, timestamps, and owners. With that map in place, you can align retention policies, access controls, and encryption with actual risk, not assumptions.

Creating a PII Catalog Proof of Concept starts with defining detection rules. Regex for common identifiers like SSNs, email formats, and phone numbers. Machine learning for language-based names and addresses. API integrations for database scanners or DLP pipelines. Store the hits in a secure datastore with audit logging enabled. Connect the catalog to visualization tools so reports update in near real time.

Measure your proof of concept by coverage and accuracy. Coverage tracks how much of your data estate is scanned. Accuracy reviews false positives and false negatives. High coverage with high accuracy means your PII detection and cataloging are ready for production scale.

Once built, the PII Catalog Proof of Concept becomes the foundation for automated compliance. GDPR, CCPA, HIPAA — the rules differ but the need is the same: know where sensitive data lives, control it, and prove you do.

You can waste weeks wiring up scanners and indexes, or you can see a working catalog in minutes. Run it now at hoop.dev and watch your PII map come alive.