ComparisonEnterprise AI Governance
Policy Gateway vs Azure AI Content Safety
Granular control vs binary filtering.
Azure AI Content Safety provides binary allow/block decisions. Policy Gateway gives you rewrite, redact, escalate, and refuse actions with structured reason codes, shadow mode testing, and safe rollouts.
Feature Comparison
| Capability | Azure AI Content Safety | Policy Gateway |
|---|---|---|
| Decision types | Allow / Block | Allow / Rewrite / Redact / Escalate / Refuse |
| Reason codes | Category scores only | Structured codes for audit trails |
| Policy-as-code | Limited (threshold config) | Full rule engine with JSON/YAML |
| Shadow mode | Not available | Log decisions without enforcing |
| Canary rollouts | Not available | Enforce on % of traffic |
| Per-user quotas | Not available | Monthly limits by user/project |
| Audit log export | Azure Monitor only | Splunk, Datadog, Elastic, S3, Azure Monitor |
| Model | Azure OpenAI only | abliterated-model with enterprise-controlled safety |
Choose Azure AI Content Safety when
- You only need binary allow/block decisions
- Your entire stack is Azure-native
- You want Microsoft-managed category definitions
- Compliance requires a first-party Azure service
Choose Policy Gateway when
- You need rewrite, redact, or escalate actions
- Teams want structured reason codes for audits
- You need shadow mode testing before enforcement
- You want full control over AI safety, not provider defaults
- Security teams need SIEM integration beyond Azure
Or switch to full control
Policy Gateway with abliterated-model gives enterprises complete ownership of AI safety—no opaque upstream filters to work around. Define exactly what's allowed and refused.
1
abliterated-model responds without built-in refusals
2
Policy Gateway applies your business rules, quotas, and audit logging
3
Security teams get full visibility and control over AI safety
Ready to see the difference?
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