Model access outside approved routes
Applications and users may call providers directly, with credentials and request content outside the organization’s approved control path.
Unmanaged AI access
Give shadow AI
a useful alternative.
Unmanaged AI often starts with a useful workflow. The control challenge is to understand the activity and offer an approved path that teams can actually use.
A governed operating modelGoverned
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01
ScopeBusiness workflow and assets
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02
ControlIdentity, policy and approvals
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03
OperateConfigured gateway and services
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04
ReviewOwners, records and evidence
Identity · Policy · EvidenceWorkflow illustration
What to look for
Understand the control gap.
Agents without clear ownership
An agent may have a useful purpose while its owner, tools and access boundaries remain unclear.
Tools outside review
MCP servers and connectors can extend what an agent can reach. A model policy alone does not define that tool boundary.
A practical approach
Build a path
you can review.
Understand your current coverage
Inventory supported cloud assets and registered services, and combine those views with the endpoint, SaaS and network controls you already use.
Make the approved path practical
Give applications governed model access and teams useful hosted agents with approved knowledge and tools.
Define boundaries before broad adoption
Assign owners, scope access, review tool capabilities and apply the inspection policies appropriate to the data.
Review what actually happened
Use available gateway records and governance reviews to understand routed activity and improve the approved path.
The product path
See the controls in context.
See AI Warden in action
Make your next AI rollout a governed one.
Bring your models, tools and security requirements. See how AI Warden puts them under one control plane.