Your AI data is on-premises. The model runs on your hardware. You call it sovereign.
Then ask: who decides which model handles a sensitive request? Where does the guardrail logic execute? Where does the telemetry from that inference request go?
For most enterprise AI deployments, the honest answers are: a vendor orchestration layer, a hosted SaaS policy engine, and an observability pipeline running in a cloud region you did not choose. The data never left the boundary. The runtime authority never entered it.
This is the control plane sovereignty problem — and it is the gap that most enterprise AI sovereignty strategies leave open.
The Residency Trap
