N8N
n8n is a workflow automation platform built for teams that want to connect AI tools, business apps, and internal data in one place. It is especially useful for technical teams because it combines a visual builder with the option to add JavaScript or Python when extra control is needed. n8n can run in the cloud or on a company’s own servers, which makes it a strong fit for businesses that care about privacy, compliance, or keeping sensitive data in-house. Its main appeal is that it helps teams build AI agents and automated workflows that are easier to test, monitor, and manage in real business settings.
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- Want to leave it? Find a replacement — see feature losses and migration risks.
Pricing
- Community Edition : Free; self-hosted
- Starter : $24 per month; 2.5k workflow executions, 1 shared project, 5 concurrent executions, unlimited users, and 50 AI Workflow Builder credits.
- Pro : $60 per month; custom workflow executions, 3 shared projects, 20 concurrent executions, 7 days of insights, admin roles, and 150 AI Workflow Builder credits.
- Business : $960 per month; 40k workflow executions, 6 shared projects, SSO/SAML/LDAP, 30 days of insights, different environments, scaling options, and Git-based version control.
- Enterprise : Custom pricing; unlimited shared projects, 200+ concurrent executions, 365 days of insights, external secret store integration, log streaming, extended retention, SLA-backed support, and invoice billing.
Features
- AI Agent Orchestration: Builds multi-step AI agents that can call tools, follow conditions, and pause for human approval when needed.
- Model-Agnostic Setup: Connects to major AI providers and open-source models, so teams are not stuck with one vendor.
- Code + Visual Builder: Lets users build workflows visually, then add code for custom logic or data handling.
- Full Execution Visibility: Shows what happened at each step, which helps with debugging, auditing, and improving results.
- Self-Hosted or Cloud: Gives teams the choice between n8n Cloud and private deployment on their own infrastructure.
- 500+ Integrations: Connects AI workflows to CRMs, databases, support tools, messaging apps, and internal systems.
Use cases
- DevOps Teams: For infrastructure alerts, deployment tasks, and internal tooling.
- IT Operations Teams: For onboarding, access requests, and support workflows.
- Security Teams: For incident enrichment, approval flows, and response automation.
- Data and RevOps Teams: For syncing systems, enriching records, and routing leads.
- Uncommon Use Cases: Used as a lightweight backend layer for small software products; used by research teams to manage experiments and labeling tasks.