Sovereign Inference Stack
Run the entire agent stack (model weights, inference, tool layer, vector stores, logs) inside a jurisdictional and operational boundary the operator controls, so no request, prompt, or output crosses into a third-party API.
Problem
A hosted-API agent sends every prompt, every tool input, and every output to a third party — that is the architecture. Contractual assurances from the provider do not satisfy regulators who require the data to stay inside a specific jurisdiction and under the operator's own keys. At the same time, the frontier hosted models offer the best capability per dollar, and self-hosting demands GPU capital expenditure and machine-learning operations skill the operator may not have. Without a deliberate stack where every load-bearing component sits inside the operator-controlled boundary, the team has to choose between being non-compliant and not shipping at all.
Solution
Choose models with permissive weights or commercial sovereign licensing. Run inference on-prem or in a jurisdictionally controlled cloud region with the operator holding the keys. Place all auxiliary services (vector store, tool gateway, audit log, evaluation harness) inside the same boundary. Document the boundary as part of the system's compliance posture (model card, data-flow diagram). Treat the boundary as load-bearing: any new tool or model call has to be reviewed for boundary impact before merge.
When to use
- Regulated workload forbids data egress to a foreign-cloud LLM provider.
- Permissively licensed or sovereign-licensed models meet quality requirements.
- The operator can run inference on-prem or in a controlled jurisdiction.
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