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Comparison

AI Workflow Automation Platform - n8n vs Make

AI Workflow Automation Platform - n8n and Make both land on Depends.

AI Workflow Automation Platform - n8n versus Make
CompareAI Workflow Automation Platform - n8nMake
VerdictDependsDepends
Best forTechnical teams building AI agentsOps teams with multi-step, branching automations
Who it's not forNon-technical teams wanting point-and-click automationAnyone needing one or two simple app connections
PrivacyMultiple maximum-severity vulnerabilities (2025-2026) and active criminal abuse . do not expose instances to the internet unpatched.²No known public vulnerabilities found in the sources reviewed.
Support qualityNo support evidence in sourcesNo support evidence in reviewed sources
Public sentimentReddit and tutorial sources show technical users and solo admins adopting it for AI automation, while security press documents exploitation of public instances.11Users praise Make's visual builder and breadth of app connections, often adopting it after hitting Zapier's limits on complex workflows.15
Biggest gotchaUnpatched instances get hijacked (Ni8mare, CVSS 10.0 RCE); patch immediately²Real monthly cost requires 'real math'; usage spikes can outgrow your plan quickly

Pick AI Workflow Automation Platform - n8n when

  • Technical teams building AI agents
  • Engineering orgs mixing code and no-code
  • Self-hosters who want data control
  • Ops teams automating multi-step processes

When AI Workflow Automation Platform - n8n is not a fit

  • Non-technical teams wanting point-and-click automation
  • Teams with nobody to patch self-hosted instances
  • Small shops needing one simple Zap, not a platform
  • Security-averse orgs uncomfortable running targeted software

Pick Make when

  • Ops teams with multi-step, branching automations
  • Teams outgrowing Zapier's complexity limits
  • Agencies building client workflows
  • Non-developers connecting many SaaS apps

When Make is not a fit

  • Anyone needing one or two simple app connections
  • Non-technical buyers wanting plug-and-play simplicity
  • Teams that hate usage-based billing surprises
  • Buyers unwilling to model credit burn before committing

Sources

  1. official
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  14. official
  15. review
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