AI model gateway with custom moderation rules: recommendations

Definition of AI model gateway with custom moderation rules: recommendations

An AI model gateway with custom moderation rules is a policy enforcement layer in front of your LLM that applies your own configurable rules, then returns both output and decision metadata.

Why AI model gateway with custom moderation rules: recommendations matters

• Custom moderation rules let you match business and legal requirements instead of provider defaults.
• Deterministic reason codes and audit exports make moderation decisions explainable.
• Shadow and canary rollouts reduce risk when moderation policies change.

How it works

• Require policy-as-code support for allowlists, denylists, flagged categories, and rewrite/redact/escalate outcomes.
• Require per-project keys and request metadata so policies can vary by app, tenant, or workflow.
• Run simulations first, then shadow and canary rollouts before full enforcement.

Runnable cURL snippet

curl https://api.abliteration.ai/policy/chat/completions \
  -H "Authorization: Bearer $POLICY_KEY" \
  -H "Content-Type: application/json" \
  -H "X-Policy-User: user-9876" \
  -H "X-Policy-Project: support-bot" \
  -d '{
    "model": "abliterated-model",
    "messages": [{"role":"user","content":"Summarize our refund policy and remove sensitive account details."}],
    "policy_id": "custom-moderation"
  }'

Example custom moderation policy

{
  "policy_id": "custom-moderation",
  "name": "Custom moderation policy",
  "owner": "Trust and Safety",
  "description": "Project-aware moderation with audit-friendly outcomes.",
  "rules": {
    "allowlist": ["product help", "refund policy", "account support"],
    "denylist": ["credential theft", "bypass security", "social engineering"],
    "flagged_categories": ["self-harm/intent", "violence/graphic", "sexual/minors"],
    "response_pattern": "rewrite",
    "rewrite_instead_of_refuse": true,
    "redact": true,
    "reason_codes": ["ALLOW", "REWRITE", "REDACT", "ESCALATE", "REFUSE"]
  },
  "org_controls": {
    "project_keys": true,
    "user_quotas": true,
    "audit_logs": true,
    "data_classification": "confidential",
    "user_quota": { "requests": 120, "tokens": 12000, "window": "daily" },
    "project_quota": { "requests": 25000, "tokens": 2500000, "window": "monthly" }
  },
  "rollout": {
    "shadow": { "enabled": true, "sample_percent": 20, "targets": ["support-bot"] },
    "canary": { "enabled": true, "sample_percent": 10, "targets": ["support-bot"] },
    "rollback_on_spike": true
  },
  "refusal_replacement": { "mode": "rewrite", "escalation_path": "policy-review@company.com" }
}

Before and after

Assistant: "I can't help with that."

Assistant: "Here is a compliant summary with sensitive details removed."
decision: rewrite
reason_code: REWRITE
policy_id: custom-moderation

Run the Policy Gateway simulator

Test custom moderation rules and decision metadata before production rollout.