Distributed discovery
Scanners across repositories and pipelines continuously feed asset evidence back into the central control plane.
Control-plane architecture
Built as a control plane, not as another dashboard
Governance AI combines a central control plane with distributed discovery and runtime evaluation to support continuous asset visibility, policy orchestration, and execution-time decisions.
Control-plane diagram
A centralized control plane with distributed enforcement and discovery
RepositoriesPipelinesAI Apps
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Governance AI Control Plane
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DiscoveryPolicyRuntime Control
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RepositoriesPipelinesAI Applications
Governance AI Control Plane
InventoryPoliciesRuntime DecisionsTelemetry
Architecture layers
From evidence ingestion to runtime decisioning
Inventory materialization
The platform correlates repositories, dependencies, prompts, tools, models, and runtime evidence into a live AI inventory.
Policy orchestration
Governance intent becomes policies, control mappings, and operational workflows instead of isolated governance artifacts.
Runtime decisioning
SDK-connected applications evaluate prompts, outputs, and tool calls with observable allow, modify, and block outcomes.
Why it matters
Built as a control layer for enterprise AI systems
This architecture supports continuous discovery, live inventory, policy orchestration, and runtime-aware governance instead of static assessments alone.
Next step
Review the architecture with your team
We can map Governance AI to your repositories, pipelines, runtime stack, and governance workflows.