Building a Team of AI Agents in n8n

Author(s): Kalash Vasaniya

Originally published on Towards AI.

In the era of AI-driven automation, teams of specialized AI agents can tackle complex projects by collaborating via modular workflows.Source: From Generated by ChatGPT AI

If you’re not a member but want to read this article, see this friend link here.

node-based workflow automation (n8n)

One agent might research data, another processes and summarizes it, and a third crafts content or makes decisions. n8n, an open-source workflow automation tool, is well-suited for orchestrating such multi-agent systems. It integrates with 422+ apps and services, allowing you to seamlessly pull in data from websites, databases, or APIs to feed into your AI workflows. In this walkthrough, we’ll break down how to build and manage a “team” of AI agents in n8n, explaining core concepts and providing practical tips you can follow.

Figure: A conceptual network of AI agents (nodes) collaborating via an n8n workflow. Each node represents an autonomous AI agent equipped with tools or APIs. In n8n, each AI agent can be implemented as a separate workflow (or sub-workflow), with each workflow performing a specific task.

An AI agent is an autonomous system that “receives data, makes rational decisions, and acts within its environment to achieve specific goals,” docs.n8n.io.

In practice, this means configuring an AI Agent node (powered by an LLM such as OpenAI’s GPT models) and connecting tool sub-nodes (like HTTP Request, database queries,… Read the full blog for free on Medium.

Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.

Published via Towards AI