Voiceflow named in Gartner’s Innovation Guide for AI Agents as a key AI Agent vendor for customer service
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With the Agent step, you can combine hard business logic with Agent networks layered on top, allowing for both risk mitigation and Agent control, as well as conversational flexibility and capability.

This component allows developers to designate specific parts of a conversation where the AI can operate independently while maintaining structured flows elsewhere in the experience.
When a user interaction reaches an Agent step, AI takes over with the ability to:
Voiceflow gives businesses a complete toolkit from Agentic networks to human-written responses and business logic to ensure you always have the right tool for the job.
Consider a customer support scenario: When a user initiates a return request, the deterministic flow handles initial validation and account verification. Once basic information is collected, the Agent step activates, allowing the AI to autonomously:
This hybrid approach ensures compliance with return policies while providing intelligent handling of complex cases. You can also create specific exit scenarios that automatically exit the Agent back to the safety of deterministic logic. These exit scenarios include situations such as an upset customer, requesting to speak with a human, or the agent detecting malicious usage outside its scope.

The addition of an Agent step eliminates the trade-off between reliability and flexibility. Deterministic flows provide consistency for critical processes, while Agent steps enable adaptability for complex scenarios—all within a unified development environment.
Voiceflow provides a practical solution for building AI Agents that balance structure with intelligence, giving you control over exactly where and when autonomous capabilities are deployed.
The Agent step's modular design supports advanced implementation patterns. Developers can connect multiple Agent steps to create sophisticated frameworks, including the widely-used Supervisor pattern where specialized agents handle different conversation aspects.
We are excited to see the novel Agent frameworks people develop using the Agent step!