A governed platform,
not a generic AI workspace
Org Systems AI treats identity, policy, and audit as first-class primitives — with IAM and RBAC, policy-driven approvals, and runtime execution controls built into every layer of the platform.
Shadow AI is a governance failure waiting to happen
Chat tools and ad hoc automations rarely have a real identity model, a policy engine, or an audit trail. Org Systems AI gives security and compliance teams the same controls they expect from any other enterprise system of record — applied to agents, workflows, and execution.
Identity & access
IAM and RBAC built in from day one
Organization-scoped identity
Every user, agent, and service credential is tied to an organization, with membership and roles enforced centrally.
Role-based access control
Deny-by-default authorization means access to projects, agents, workflows, and data is granted explicitly, not assumed.
Vaulted credentials
API keys and secrets are encrypted at rest and accessed through governed reference patterns, never exposed in plaintext.
Policy & approvals
Human-in-the-loop where it matters
Policy-driven controls
Define what agents and workflows are allowed to do — by capability, by connector, by data boundary — and enforce it before execution, not after.
Mandatory approval gates
Route sensitive actions through human approval before an agent can send data externally, spend budget, or take an irreversible step.
Deny-first resolution
Model routing and execution decisions resolve against policy first — capabilities are only available where governance explicitly allows them.
Immutable decision records
Every policy resolution and routing decision is recorded immutably, so approvals and denials are always explainable after the fact.
Audit & observability
Every action is observable, every decision is traceable
Governance controls are only as strong as the visibility behind them. Org Systems AI links every policy decision, approval, and execution event to the audit and observability layer, so security teams can review who did what, when, and under which policy — across every runtime node.
See how observability ties in →Full execution event history, correlated to identity and policy. Immutable audit trails for approvals, denials, and overrides. Cross-node visibility into agent behavior for compliance review.
Runtime trust
Execution controls across every runtime node
Scoped execution tokens
Desktop, browser, and cloud runtime nodes operate under short-lived, capability-scoped tokens rather than standing credentials.
Capability allowlisting
Runtime nodes can only exercise the specific capabilities an admin has explicitly allowed for that agent or workflow.
Zero-trust boundaries
Every execution lease is validated against policy at claim time, keeping runtime infrastructure honest even at scale.
What governance actually buys your organization
Confident AI adoption
Roll out AI across departments without waiting for security to say no — the controls are already there.
Audit-ready by default
Answer compliance and regulator questions from real records instead of reconstructing history after an incident.
Consistent policy everywhere
One policy model governs AI Hub, AI Control Center, and every runtime node in the Agent Runtime Network.
Talk to us about your security and compliance requirements
Our team can walk through IAM, policy, and audit architecture with your security and compliance stakeholders.