Private agent operations

How can a company run AI agents with full data sovereignty?

A company can improve data sovereignty by placing agent runtimes, tenant state, credentials, storage, logs, and network access inside infrastructure it controls, then limiting external connections through explicit policy. Bewize supports this operating model through private deployment patterns and Hermes Hub controls, but it does not promise absolute privacy or a compliance outcome.

A sovereignty checklist

Define the boundary before selecting models or workflows.

Own the runtime boundary

Choose private cloud or data-center placement for the managed agent runtime.

Separate tenants

Keep identity, workspaces, secrets, sessions, and logs tied to the tenant that owns them.

Control credentials

Manage secret metadata and environment keys without casually exposing raw values.

Inspect evidence

Use run history, policies, access state, and redacted metrics to review operations.

Related controls

Hermes Hub

Tenant lifecycle, policies, secrets, storage, schedules, and runtime operations.

Learn more

Data sovereignty FAQ

Does data sovereignty require an on-premise LLM?
Not necessarily. Runtime placement, data handling, and model hosting are related but distinct architecture decisions.
What does Bewize keep under the operator boundary?
The deployment model can keep runtime placement, tenant state, credentials, storage, logs, schedules, adapters, and access state under enterprise operations ownership.
Is sovereignty the same as guaranteed security?
No. A controlled deployment boundary is one part of governance; it is not an absolute security or compliance guarantee.

Plan a sovereignty boundary

Map runtime placement, data paths, credentials, storage, and review evidence for your agent deployment.

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Architecture conversation

Tell us what your team needs to control

Share your deployment boundary, number of agents, work surfaces, and governance requirements. We will reply by email to arrange a focused technical discussion.

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