ElevenLabs Launches Agent Workflows — Its Own Take on n8n for Conversational AI
Voice technology leader ElevenLabs has unveiled a new automation platform called Agent Workflows — a visual builder that allows developers to create sophisticated conversational AI systems with branching logic, subagents, and human handoff capabilities.
A new era of modular AI design
Agent Workflows brings a **drag-and-drop interface** similar to workflow tools like **n8n** or **Node-RED**, but focused entirely on conversational intelligence. Users can define **decision trees, tool invocations, and multi-agent interactions** in a single unified environment.
The system introduces multiple node types that enable deep customization of agent behavior:
- Subagent: modifies the personality or specialization of the AI for specific tasks.
- Tool: invokes external APIs, functions, or integrated systems.
- Agent Transfer: passes control between different agents to manage multi-turn conversations.
- Transfer to Number: hands off the session to a human operator through telephony or contact center systems.
Each subagent comes with its own **system prompt, knowledge base access, and tool permissions**, giving teams granular control over how an AI responds across different scenarios.
Bridging automation and conversation
Unlike traditional voice assistants, ElevenLabs’ Agent Workflows are designed for **enterprise-grade conversational orchestration**, combining speech synthesis, context management, and custom logic. The platform lets organizations map out how AI agents should handle queries, escalate to specialists, or trigger real-world actions.
According to ElevenLabs, the framework’s goal is to enable **adaptive, human-like conversation flows** that maintain accuracy across complex tasks such as customer support, media production, or research automation.
Designed for collaboration and scalability
The platform supports **multi-agent ecosystems**, where each subagent can specialize in different domains — from marketing and sales to technical troubleshooting or analytics. Developers can also configure rules determining when control shifts between agents or human operators.
This modular architecture makes Agent Workflows particularly suitable for **large-scale deployments** in call centers, automated media studios, and educational platforms, where the blend of human and synthetic voices must remain seamless.
Part of ElevenLabs’ broader strategy
Agent Workflows is the latest addition to ElevenLabs’ expanding suite of AI tools, which includes **voice cloning**, **speech synthesis**, and **audio dubbing** technologies already used by major media and gaming companies. By venturing into orchestration and automation, ElevenLabs is positioning itself as an **end-to-end AI interaction platform**, not just a voice provider.
The integration of these new tools could mark a shift toward a future where **entire conversational pipelines — from voice to logic — are managed within one ecosystem**.
Comparison with n8n and open alternatives
While open-source tools like n8n already offer flow-based automation, ElevenLabs’ advantage lies in its **native voice integration and language modeling**. Developers can combine speech recognition, emotional tone, and workflow logic without relying on third-party connectors.
That said, the company’s closed ecosystem may limit customization for open-source purists — a trade-off between convenience and transparency that continues to shape the enterprise AI landscape.
Conclusion
With Agent Workflows, ElevenLabs steps into the **low-code AI orchestration arena**, bridging the gap between conversational design and automation. The move demonstrates how voice-first companies are expanding into full-stack agent management — where every dialogue, decision, and escalation can be mapped visually and optimized through data.
As AI assistants evolve from simple bots to autonomous collaborators, tools like Agent Workflows may define the next generation of **interactive, human-centered artificial intelligence.**
Editorial Team — CoinBotLab