Design-partner pilots for AI agent conversation governance

Overview

Quickstart

Add a control layer before an AI agent sends a risky response, calls a tool, or triggers downstream workflow action.

turnkeeper.ai sits between the agent and the action. Your application sends the proposed action, relevant transcript context, and workflow metadata. turnkeeper returns a decision: allow, review, block, or audit.

Primary benefit

Routine policy checks can resolve before another model call. High-risk moments move to review with context, while safe actions continue without adding unnecessary LLM usage.

  1. Send a proposed action before the agent replies or calls a tool.
  2. Receive allow, review, block, or audit as the control decision.
  3. Continue, route, or stop the workflow with a linked audit event.