Keep your AI rollout within approved intent.

Know what agents can do across your connected environment, resolve consequential authority gaps before rollout, and keep control as their reach and behavior change.

Know the connected agent surface before rollout.

Know how an agent, its identity, tools, permissions, and connected workflows combine into production authority—even when the path crosses platform and cloud boundaries.

Understand Microsoft agent authority

See how connected Microsoft Foundry and Entra evidence links agent purpose with service principals, managed identities, permissions, and OAuth grants.

Understand AWS reach

Know how connected workload identities, IAM roles, trust relationships, and available runtime activity expose production resources.

See cross-system reach

Trace authority into connected workflow, SaaS, data, and proprietary systems. Confirm the integration and evidence scope for your environment.

Know what is ready for production.

See which agents and agentic workflows can reach consequential actions, whether that authority matches the owner-approved scope, and what must change before rollout.

Know the agent surface

Find agents, configured authority, and observed execution across connected identity, cloud, AI, workflow, and application systems.

Find consequential drift

Identify authority or behavior beyond approved purpose. Where intent is missing, ask the accountable owner to confirm it.

Correct with approval

Model the correction, preserve approved work, and initiate the human-approved work through customer workflows.

Keep authority governed

Re-evaluate the decision as authority, observed behavior, ownership, or approved purpose changes.

Catch what blocks production readiness.

Find the conditions that turn a routine rollout into an access, operational, or governance problem.

Find missing ownership

An active agent or non-human identity no longer has a valid business or technical owner.

Identify excess authority

Roles, grants, or downstream access exceed the job approved for production.

Review cross-system reach

Individually allowed steps combine into a consequential action that was never reviewed end to end.

Catch drift after approval

Observed activity, configured reach, or ownership changed after the last approval.

Decide which authority needs control before rollout.

Compare authority, execution, ownership, and owner-approved scope. Return the recommended action, the reason, and the expected impact.

Example rollout decision · Modeled impact

Constrain

Remove the unintended trust relationship before rollout.

Why: It lets the agent invoke a production action outside its owner-approved scope.
Expected to stop: The unapproved production action.
Expected to preserve: The approved workflow.
Disposition: Initiate the approved work through customer workflows.

Give each team an answer it can use.

Replace disconnected findings with prioritized agent access decisions that security, identity, cloud, AI platform, workflow, and application teams can execute together.

Know the surface in scope

Agents and workflows visible in connected evidence, with configured authority, observed behavior, ownership, approved purpose, and cross-system paths.

Prioritize the control decisions

Approve, Constrain, Reject, or Unknown, with the reason, accountable owner, lowest-impact supported correction, and expected change impact.

Preserve legitimate work

See what should stop, what should keep working, and what may remain before access changes.

Act through your systems

Initiate approved work through customer workflows and route the decision into existing security and operations processes.

Keep policy and approval in your control.

Keep your policy and approval rules in control. Initiate approved work through customer workflows for your authorized teams to apply, then reassess as authority, observed behavior, ownership, or approved purpose changes.

See access-change impact modeling →

Validate rollout readiness.

Start with a bounded, read-only connection to the relevant environment. Evaluate every agent and workflow visible across that environment, get prioritized decisions, and prove value before a broader rollout. No per-agent instrumentation.