Case studyArchitecture, governance, and how to adapt this pattern in a pilot
Business use case
If your policy says “don’t paste Restricted data into external AI tools,” you need a guardrail that works before the model call.
Solution
A local redaction pass (regex + heuristics) that replaces obvious emails/phones/cards and returns a findings report. Pair it with an approval gate for any remaining “Restricted” content.
Delivery playbookDiscovery → pilot → scale
- 1Discovery2–4 wks
Define Restricted/PII patterns and acceptable false-positive rate with risk and privacy.
- 2Pilot6–8 wks
Apply redaction to all prompts; log findings and review misses weekly.
- 3Scaleongoing
Add DLP integration, allow lists, and user training; enforce policy centrally via gateway.
Where else this appliesRedaction is a practical way to align “don’t paste Restricted data” policies with reality: users will paste it unless you intercept it.
Support intake
Redact emails/phones before messages are summarised or routed by a model.
Meeting notes
Scrub transcripts before extracting actions and decisions.
Ticket enrichment
Protect sensitive identifiers in batch triage pipelines.
Internal copilots
Reduce accidental leakage from staff-facing chat assistants.
Local processing avoids sending raw PII to external APIs. Pair with enterprise gateways and logging for compliance.