AI Boundary Protection
Pre-egress data and trust-boundary enforcement on governed AI pathways—not post-hoc leakage detection alone.
Overview
AI Boundary Protection constrains what data and trust-bound content may cross AI pathways before external provider contact. The AI Boundary Engine applies ALLOW, MASK, REDACT, REQUIRE_APPROVAL, QUARANTINE, and BLOCK outcomes as enforcement mechanism—complementing AI Data Governance domain policy with pre-egress controls on the Universal AI Gateway.
Governance workflows
- Boundary policy management and Provider Trust Registry
- Pre-egress evaluation on governed gateway traffic
- Merged outcomes with AI Data Governance (strictest wins)
- Operator-visible boundary evidence and replay linkage
Runtime supervision
- Fail-closed when boundary evaluation fails (configurable)
- Residency and classification signals on AI egress paths
- MCP, tool, and agent context in boundary evaluation
- Separate from enterprise data catalog scope
Enterprise deployment
- Tenant-scoped boundary policies and trust registry
- Included in CGOS commercial governance packages
- Honest scope: governed gateway traffic—not all consumer AI use
Auditability & evidence
- Boundary evidence for pre-egress decisions
- Linked from DATA-GOV access evidence where applicable
- Governance replay and operator investigation paths
Operational capabilities
- Pre-egress boundary enforcement
- Provider trust and residency context
- Enforcement mechanism paired with AI Data Governance domain
- Not autonomous legal classification or certified DLP claims
Operational boundaries
NerveMind CGOS provides operational governance infrastructure — awareness, traceability, and human authority — not autonomous legal interpretation or certification claims unless explicitly stated in a signed agreement.