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n8n vs Relevance AI

A plain-English comparison to help you choose between them.

01VERDICT

Control versus speed, stated plainly. Pick n8n when you want to own the machinery: open source and self-hostable, with data residency and compliance following from your own infrastructure, real code steps when visual nodes run out, and execution-based pricing that keeps volume cheap. Pick Relevance AI when the goal is delegating work to agents this month, without code: a managed platform where autonomous agents and multi-agent teams cover research, outreach and operations, with bring-your-own-key economics keeping usage visible.

02AT A GLANCE

Side by side

Summary

n8n is the engineer's automation platform: open source and self-hostable, with execution-based pricing that keeps high-volume workflows economical, visual nodes that accept real code when logic demands it, and first-class support for AI and agentic flows.

Best for
  • Self-hosted automation with data residency
  • Execution-based pricing at high volume
  • Visual flows with real code where needed
Cost
Freemium (Free tier + paid plans)
Ease
Openness
Runs privately (self-hostable)
Data
Execution-based pricing (whole workflow = one execution) is usually cheaper than per-task, but AI Workflow Builder credits (50 Starter / 150 Pro) and any LLM API calls you wire in are metered separately, and Business overage is roughly €4,000 per 300,000 extra executions. The sticker price is not the whole bill. Self-hosting shifts cost to your own infrastructure/maintenance.
Summary

Relevance AI is a no-code platform for building an AI workforce: autonomous agents assembled from tools, triggers and instructions, deployed against real work such as outreach, research and operations tasks.

Best for
  • Building autonomous agents without code
  • Multi-agent teams coordinating on real work
  • Bring-your-own-key model cost control
Cost
Freemium (Free tier + paid plans)
Ease
Openness
Hosted service
Data
Agents act across connected business tools; treat credential grants as the security boundary they are.
04FAQ

Common questions

n8n supports agentic flows too, so why buy an agent platform?

Because the products centre different things. n8n gives you first-class AI and agent nodes inside workflows you design, host and operate, which suits teams who want agents as components under engineering control. Relevance AI makes the agent the product: assembled from tools, triggers and instructions, deployed as a workforce without anyone running a server. If nobody on the team will own infrastructure, that answers it.

Which gives better cost control?

Both are unusually transparent, differently. n8n is free to self-host, with hosted plans priced by executions, so high-volume workflows stay economical and the marginal run costs little. Relevance AI lets you bring your own model keys and watch usage directly, but always-on agents consume steadily and consumption climbs with autonomy. Model a fleet's economics before it runs unattended; meter a workflow's volume before it scales.

What does each demand of the team?

n8n demands an owner: someone to run the server, apply updates and secure a platform holding credentials to every connected system, in exchange for residency and control. Relevance AI removes the infrastructure but not the supervision: agent autonomy is earned the way a new hire earns it, with narrow scopes and review before trust. Neither is a set-and-forget purchase.

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Tool facts last checked July 2026

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