Control Layer for AI Agent Conversations

The control layer for AI agent conversations

Route risky AI outputs and workflow actions through policies, approvals, transcripts, and audit-ready logs.

Policy match detected
Routed to human review
Approved response logged
Customer Support
Lead Qualification
Appointment Booking
Account Onboarding

Conversation Governance

Policies, approvals, transcripts, and logs for AI agent conversations

Evaluate risky AI outputs

Check each proposed response and workflow action against policy before the agent replies or triggers downstream work.

Route human approvals

Send high-risk conversation turns to the right reviewer with the transcript, policy match, and proposed answer attached.

Keep audit-ready logs

Capture every policy match, review decision, approval, block, exception, transcript, and outcome for later review.

Risky response routed to review

A policy match paused the agent response and attached the transcript, proposed answer, and approval options.

Review queue
Coverage denial explanationPolicy: regulated advice
Review
Refund exception responsePolicy: manager approval
Escalate
Patient intake summaryPolicy: sensitive data
Approved
Loan payoff guidancePolicy: prohibited claim
Blocked

Human-in-the-loop controls

AI agents move fast. Regulated workflows still need custody.

When AI starts speaking to customers, quoting policies, or triggering downstream tasks, turnkeeper.ai gives teams intervention points they can trust.

Policy engine

Define when agents can respond or must stop.

Set the rules that decide when an agent can answer, ask a clarifying question, route to review, approve, block, or stop.

Review queue

Keep approvals next to the AI conversation.

Give reviewers the transcript, policy reason, proposed response, and decision history in the same workflow.

Decision logs

Make every escalation audit-ready.

Record policy matches, reviewer actions, response versions, approvals, blocks, exceptions, and final outcomes.

Outcome analytics

Measure policy matches and exceptions.

Track what triggered, who approved it, where risk was prevented, and where guardrails need better thresholds.

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