Platform capabilities
Runtime governance infrastructure for autonomous AI systems — explore the CGOS platform surface with operational, policy-aware, enterprise-grade depth.
Platform capabilities
- Runtime Governance
Pre-execution policy enforcement, authorization, and fail-closed runtime control for AI workloads.
- AI Governance Engine
Deterministic policy and authority evaluation at runtime—catalog-backed, tenant-scoped, explainable.
- AI Agent Governance
Lifecycle control for autonomous agents—registry, scope contracts, containment, and revocation.
- AI Data Governance
Govern the data AI applications and agents are authorized to access and use during execution. Apply registry-based policies, resource bindings, provider restrictions, residency controls, runtime masking/redaction, audit and governance replay.
- AI Boundary Protection
Pre-egress data and trust-boundary enforcement on governed AI pathways—ALLOW, MASK, REDACT, block, and escalate before provider contact.
- Human-in-the-Loop
Non-bypassable human authority gates for elevated-risk AI actions—fail-closed approval workflows with evidence.
- Policy Engine
Enterprise policy binding, lifecycle management, and runtime integrity with fail-closed semantics.
- AI Governance Control Plane
Central runtime control plane for identity, policy, boundary, authority, execution, and evidence across AI workloads.
- Audit / Evidence
TAP lineage, governance evidence, replay, and export paths for assurance and regulatory review.
- Runtime Intelligence
Operational intelligence for governed runtimes—signals, posture insight, and operator-visible telemetry.
Extended platform modules
AI Data Governance governs data on AI execution pathways—not general-purpose enterprise data catalog scope. See /ai-data-governance-vs-enterprise-data-governance for the distinction. All platform modules remain fully routable and indexable.