Separate tenant state
Review how runtime state, workspaces, credentials, sessions, logs, and storage are associated with each tenant.
Sensitive data
How do I protect sensitive data in an AI agent deployment?
Protect sensitive data in an AI agent deployment by defining tenant identity, storage, credentials, policy boundaries, browser isolation, access blocking, and operational evidence before agents handle real work. Bewize names these as source-backed controls in Hermes Hub; they are not a universal security, privacy, or compliance guarantee.
A data-protection review checklist
Evaluate concrete boundaries instead of relying on broad assurances.
Control secrets and policy
Keep managed secret metadata, environment keys, and available capabilities under operational control.
Inspect and stop work
Confirm that operators can review run history, redacted metrics, access state, and stop or recovery paths.
Sensitive-data protection FAQ
What controls should buyers inspect first?
Start with tenant isolation, runtime ownership, managed credentials, policy boundaries, storage, browser behavior, access blocking, and run evidence.
Does Bewize claim 100% security?
No. Bewize public copy should name concrete controls and evidence rather than absolute security claims or unsupported certifications.
How should browser data be handled?
When browser work is required, review the tenant-scoped Browser Sidecar boundary alongside profiles, artifacts, credentials, and policy.
Review sensitive-data controls
Discuss tenant isolation, credentials, storage, browser boundaries, policy, and operational evidence.
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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