compliance_monitoring · saas · workflow
Meta scales Privacy Aware Infrastructure (PAI) to embed privacy controls across GenAI product development
GenAI products introduce novel data types, dramatically increased data volumes, shifting privacy and compliance requirements, and faster development cycles that strain existing privacy infrastructure.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · User interaction generates data
User-interaction data from AI glasses requires a complete map of its movement to maintain privacy requirements.
Tools used
PrivacyLibPolicy Zoneslarge language model (LLM)
Outcome
PAI supports thousands of microservices and product teams across Meta's ecosystem, providing auditable real-time insight into every data flow and enabling Meta to launch GenAI products like AI glasses at global scale with verifiable privacy guarantees.
Grounding & classification
Source type: technical build writeup
15 fields verified against source quotes, 2 dropped as unverifiable.
data extractionnamed customertools describedworkflow describedsoftwareautomation ratetechnical build writeupback office opscompliance monitoringdata sync enrichmentmonitor detect alert