Governance & Policy Engine
Define policies once. Enforce them everywhere.
Write governance rules as code. Set risk tiers, require approvals, mandate documentation, and prohibit unsafe behaviors — then watch them enforced automatically across every team and cloud.
Policy Editor
when model.risk_tier == "high":
require approval:
- ml_lead # SLA: 48h
- caio # SLA: 5 days
mandate:
- impact_assessment
- data_lineage_complete
- eu_ai_act_annex_iii_check
prohibit:
- production_deploy_without_approvalPolicy-as-code
Governance rules live in Git alongside your software — versioned, reviewed, tested, and deployed like any other code.
Automated risk scoring
Risk tiers assigned based on your criteria: data sensitivity, model type, EU AI Act category, deployment context.
Immutable audit trail
Every policy decision, approval, and override is cryptographically logged — tamper-evident and regulator-ready.
Policy-as-Code
Governance rules that live where your code lives.
Write policies in WiseRegent's declarative YAML DSL. Store them in Git. Review them in pull requests. Deploy them through your existing CI/CD pipeline. When policies change, the audit trail captures why, who approved it, and when it took effect.
- YAML-based policy language: human-readable, expressive, and diff-friendly.
- Git-native workflow: PRs, approvals, and rollback for every policy change.
- Dry-run mode: preview which assets would be affected before deploying a new policy.
Policy Deployment
high-risk-model-deployment.yaml
# Dry-run output:
✓ fraud-detection-v3 → approval required
✓ gpt-4o-assistant → approval required
customer-seg-v1 → no change (low risk)
churn-predictor → no change (low risk)
2 assets affected · Deploy? [y/n]Approval Workflows
The right people approve AI before it ships.
WiseRegent routes each asset through the correct approval chain based on its risk tier. Low-risk models self-approve; high-risk models wait for ML lead and CAIO sign-off. SLAs are tracked, escalations are automatic, and nothing slips through.
- Risk-tier routing: approval chain determined automatically from policy, not ad hoc.
- SLA enforcement: reviewers notified, escalations triggered, SLA breaches logged.
- Delegation and override: controlled exceptions with mandatory justification and audit record.
Approval Queue
3 pending · 1 escalated
Consistent governance from the first commit to production.
Write
Author policies in YAML and commit them to Git.
Deploy
Policies activate automatically — no downtime, no scripts.
Enforce
Gates fire on every asset register, update, and deploy event.
Audit
Every decision captured in an immutable, exportable log.
Enforce across
Policies enforced wherever AI runs
Early access open
Govern your AI agents
before your auditors do.
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