
n8n connects applications and AI steps in visual workflows. Technical teams can combine prebuilt nodes with custom API calls and code, then inspect how data moves through each step. The platform supports managed cloud hosting and deployment on your own infrastructure.
The canvas shows individual steps while allowing code where visual configuration is insufficient. Teams can inspect prompts, responses, and execution data rather than treating an agent as an opaque process. Self-hosting offers deployment choice, but still requires managing infrastructure and access controls.
Build workflows around app integrations, model calls, and data processing. n8n supports AI agent workflows, retrieval-augmented generation, and MCP connections. Human approval steps and rule-based logic can constrain actions before they reach other services.
For debugging, re-run individual steps, replay or mock input data, and inspect execution logs. The same workflow can mix visual nodes with custom logic. These controls help test an automation against realistic inputs before relying on it for business operations.
For an evaluation, try a workflow involving your actual apps and error cases. Consider how easy it is to inspect failures and maintain custom code. Deployment flexibility is useful, but it does not remove the effort of monitoring integrations and managing a self-hosted instance.
The self-hosted community version is available without a software fee for uses allowed by the Sustainable Use License, including internal business use. Hosting and external service costs remain separate. n8n calls its model fair-code and source-available, rather than OSI open source. Managed cloud and enterprise offerings have commercial plans; compare their execution allowances and features before choosing.
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It connects apps, data, and AI steps in visual workflows, with custom code, API calls, and human approvals where needed.
The self-hosted community version has no software fee for uses allowed by its license. Hosting and external API costs are separate.
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