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AI Guardrails & Governance

Turn AI policy into safeguards teams can manage and prove.

Detect sensitive data, apply policy checks, manage access, and keep a complete record of AI usage and guardrail events. Give governance teams the evidence they need for review.

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Solution Brief

TRUSTED BY ENTERPRISE DATA TEAMS WORLDWIDE

Govern every AI interaction where it happens: on the trace.

Six controls connect policy enforcement, monitoring, and evidence.

Sensitive-data and PII detection

Detect sensitive data such as PII in inputs and outputs. Surface exposure risk in the same trace where it occurred.

Topic restrictions and policy checks

Apply topic restrictions or policy checks where needed. Capture guardrail failures as part of the trace and evaluation workflow.

Role-based access and tenant isolation

Scope observability data by environment, sensitivity, project, tenant, and role so teams see only the AI interactions they are authorized to access.

Complete AI usage audit trail

Record who ran what, against which system, when it happened, and what changed. Preserve the context governance teams need without manual reconstruction.

Retention, registry, and risk classification

Set retention windows for traces, evaluations, and guardrail events. Link each AI system to its owner, approved deployment, metadata, and risk tier.

Compliance reporting and alerts

Build saved governance reports and trigger alerts on policy, safety, or quality breaches with the underlying trace and evidence ready for review.

From policy definition to audit-ready evidence in four steps.

Define

Configure sensitive-data detection, topic restrictions, retention, access roles, and risk classifications for each system or project.

Apply checks

Evaluate inputs and outputs for sensitive data and policy violations. Record results and guardrail failures on the trace and in the evaluation workflow.