Secure Enterprise Boundaries
The architectural perimeter within which private AI runs: ownership, access, identity, evidence, and control designed as one structure.
Secure Enterprise Boundaries describe the architectural perimeter within which Private AI systems run: ownership, access, identity, evidence, and control designed as one structure rather than assembled from separate products.
Inside the boundary, sensitive data and regulated workflows operate on infrastructure the enterprise owns. Models are served locally, identity is enforced at every crossing, and every access leaves evidence. Outside dependencies are explicit and countable, not accidental. The boundary is what makes the difference between AI you use and AI you own.
For regulated industries, Secure Enterprise Boundaries are the precondition for AI adoption at all: HIPAA, CMMC, GLBA, and NERC CIP environments cannot rely on a third party's terms of service as their perimeter. The boundary must be theirs.