AI Security & Trust
Clear boundaries on how Opinnate AI handles data, protects access, and delivers explainable outputs—so enterprises can adopt AI with confidence
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Security & Compliance
Policy enforcement and governance
Clear boundaries (AI Security & Trust)
Request
Data sent to the cloud (for interpretation & response formatting)
- The user’s query text is sent to the cloud AI engine so it can be interpreted and the response can be returned in a useful format.
- Only the minimum required context should be included (e.g., identifiers, summaries, or relevant excerpts) to answer the question accurately.
- Secrets and credentials are not required for this flow and should never be included in prompts or context payloads.
Private
Data not intended to be sent
- Firewall/admin credentials, private keys, and authentication tokens
- Full raw configuration dumps unless explicitly required by the use case
- Unnecessary personally identifiable information (PII) — keep queries/context sanitized when possible• Unnecessary personally identifiable information (PII) — keep queries/context sanitized when possible
Authorization
Access control
- Access to AI features should follow your existing role-based access model (who can ask, who can approve, who can execute).
- Sensitive contexts can be restricted by scope (device, environment, tenant, business unit) to prevent overexposure.
Traceability
Logging & auditability
- AI interactions can be captured as auditable events (who asked what, when, and what context was used).
- Recommendations and proposed actions should keep evidence references (rules/objects/usage/topology) so decisions are reviewable.
- When actions are applied through workflows, the system should retain a traceable change trail (request → review/approval → outcome).
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