Runtime Governance defines how TealTiger enforces governance at execution time for agentic AI systems.
The Runtime Governance Hub defines normative execution‑time controls for policy enforcement, decision evaluation, and evidence generation
While governance foundations establish principles and contracts, runtime governance ensures those rules are actively enforced when agents invoke models, call tools, access data, or produce side effects.
This hub focuses on deterministic enforcement, fail‑closed behavior, and audit‑grade evidence generation during live execution.
What This Hub Covers
- Execution‑time enforcement of governance contracts
- Deterministic allow / deny / approval decisions
- Fail‑closed behavior under uncertainty
- Tool, data, and side‑effect control
- Runtime evidence generation for audit and compliance
Why Runtime Governance Matters
Without runtime enforcement:
- Policies remain advisory
- Guardrails can be bypassed
- Risk accumulates silently
- Evidence is incomplete or post‑hoc
TealTiger treats runtime governance as the last line of defense—where governance intent becomes enforceable system behavior.
Core Articles
- Runtime Governance
- The primary runtime governance model for enforcing contracts, boundaries, and evidence at execution time.
Additional Articles
- Runtime Governance: What Must Be Enforced
- Fail‑Closed AI Systems: Governance Under Uncertainty
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Why Observability Is Not Governance
Related Insights
These Insights explain how runtime governance controls interact with risk signals and enforcement outcomes:
- From Risk to Runtime: How Governance Enforcement Actually Works
- AI Risk Signals from Runtime Telemetry
These articles deepen runtime governance by clarifying what must be enforced, how uncertainty is handled safely, and why observability alone cannot satisfy governance or audit requirements. or audit requirements**.