Control what AI may do—and when people decide.

Claire operates inside configured permissions, business rules, and escalation boundaries. Teams define the work, the evidence required, the actions permitted, and the moments that require human judgment or approval.

Identity & accessRole, workflow, tool, record, and field-level boundaries

Decision policyRules, thresholds, approvals, and prohibited actions

Human controlReview, exception routing, takeover, and final accountability

TraceabilityInputs, tool activity, state changes, outputs, and handoffs

Operating controls

Govern the workflow, not just the model.

Reliable operations require controls around the complete chain of work: who initiated it, which data was retrieved, which tools were called, why a route was selected, and what happened next.

Bounded access

Grant only the minimum systems, functions, records, and fields needed for a defined workflow.

Configured decisions

Apply organization-specific eligibility, routing, service, risk, and approval rules before action.

Visible exceptions

Route ambiguity, risk, emotional situations, policy conflicts, and professional decisions to named owners.

Change control

Version prompts, tools, rules, and workflow definitions; test changes before increasing responsibility.

Operational evidence

Preserve the inputs, outputs, tool calls, policy results, approvals, and final disposition of each case.

Continuous review

Monitor completion, exception, override, and escalation patterns to find unsafe or inefficient behavior.

Responsibility model

Automation does not remove accountability.

Claire prepares, coordinates, and completes permitted work. Your organization retains responsibility for policy, professional judgment, authorization, and outcomes.

Claire can prepareGather context, validate required fields, retrieve records, and assemble the next action.
Claire can executeComplete actions explicitly permitted by the workflow and the authenticated user’s authority.
People approveClinical, legal, financial, safety, high-risk, or otherwise designated decisions.
Owners improveReview exceptions and outcomes before expanding the workflow’s scope.

Design the boundary before launch

Every automated action needs an owner, permission, failure path, and completion definition.

Governance becomes operational when it is expressed inside the workflow. A policy document alone cannot decide what happens when a record is ambiguous, an API times out, an action exceeds authority, or a person does not respond before an SLA expires.

Define the trigger

Identify who or what may start the workflow: an inbound call, message, form, approved campaign, system event, or operator. Record the source and available identity context.

Limit retrieval and action

Specify necessary systems, records, fields, tools, and actions. Separate read from write, preparation from execution, and routine actions from approvals.

Make decisions inspectable

Use explicit branches, decision routes, time checks, required fields, variables, and policy results so operators can understand why a path was selected.

Design failure behavior

Define retries, timeouts, unavailable-system behavior, incomplete-information handling, duplicate detection, escalation ownership, and customer communication while resolution is pending.

Human-in-the-loop states

“A human is involved” is not specific enough.

Different situations need different control patterns and a defined path back into the workflow.

Human approvalClaire prepares an action; an authorized person approves or rejects it before execution.
Human decisionClaire assembles facts and routes a judgment that should not be automated.
Human takeoverA person assumes the live conversation with transcript, context, and actions attempted.
Escalate on exceptionThe normal path remains automated until ambiguity, risk, conflict, or failure crosses a threshold.
Return to ClaireAfter a decision, the workflow resumes follow-up, system updates, confirmation, and closure where supported.

Governance questions

What teams should settle before deployment.

Who is accountable for an automated outcome?

The organization remains accountable for policy, permissions, professional decisions, and outcomes. Automation does not transfer responsibility.

What should be logged?

Preserve the trigger, identity context, data retrieved, state changes, policy result, tool actions, communications, handoffs, approvals, failures, and final disposition available to the workflow.

How should a team expand autonomy?

Start bounded, test normal and failure paths, monitor outcomes and overrides, correct recurring exceptions, then expand permissions only when evidence supports the change.

Operational review

Use exceptions as evidence for improvement.

Review why a workflow stopped, why a person overrode it, which records were missing, which system calls failed, and whether the final disposition matched policy. Repeated exceptions may indicate a configuration change, an integration requirement, a product gap, or a decision that should remain human. Governance is not a one-time checklist; it is the operating discipline that determines whether responsibility should expand.

Bring us one controlled workflow.

We will map its permissions, decision boundaries, approval points, and audit requirements.

Book a workflow demo