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n8n is an AI workflow automation platform designed for technical teams that need flexibility without architectural constraints. It provides a visual canvas for building automation workflows while simultaneously supporting custom code in JavaScript or Python at any step. Teams can connect to over 500 pre-built integrations and use custom API connections for anything beyond that catalog.
The platform supports building AI agents and multi-agent systems, RAG (retrieval-augmented generation) pipelines, and human-in-the-loop workflows where structured approvals and guardrails govern AI actions. Users can enforce structured inputs and outputs to control data flow to and from AI steps, and combine rule-based automation with AI decision-making in a single workflow.
n8n is available as a cloud-hosted service or as a fully self-hosted deployment using Docker, giving organizations the choice to keep data on-premises. The open-source codebase is accessible on GitHub, and the platform includes enterprise-grade security capabilities: SSO SAML and LDAP, RBAC permissions, encrypted secrets, audit logs with log streaming, version control through Git, and isolated environments for development, staging, and production.
Debugging and observability are built into the editor: users can re-run individual steps, replay or mock external data, inspect inputs and outputs at every step without extra clicks, and use the native logs view to trace issues. AI workflows can be evaluated natively to optimize accuracy before reaching production.
- Automate employee onboarding processes across HR and IT systems without manual steps
- Enrich and triage security incident tickets by connecting threat intelligence data sources
- Convert natural language queries into structured API calls for developer operations workflows
- Generate customer insights and summaries from review data for sales teams
- Build and deploy multi-agent AI systems that handle complex, multi-step reasoning tasks
- Set up RAG pipelines connecting internal knowledge bases to AI models for accurate responses
- Automate lead management and CRM updates triggered by inbound activity signals
- Create IT operations workflows that respond to infrastructure alerts and tickets automatically
- Develop backend prototypes and API endpoints without dedicated backend infrastructure
- Embed automation capabilities directly into SaaS products for end-user workflow execution
- Sync and transform data between disparate business applications using 500+ pre-built nodes
- Monitor and evaluate AI agent performance using native testing and evaluation tools
