Is n8n or Relevance AI cheaper?

n8n starts at About $24/mo (Cloud Starter, 2,500 executions; roughly $20 on annual billing) (free plan available). Relevance AI starts at Free (200 Actions per month); Pro from $19 per month billed annually (free plan available).

n8n vs Relevance AI

An independent, review-free comparison compiled by the SaaSTracker editorial team. Both products are profiled in full, and neither can pay for placement here.

The short answer

Editorial assessment

Relevance AI compared with n8n

n8n is the engineer's answer: self-hostable, source-available, no per-Action meter, and with AI agent nodes that cover a good share of what Relevance AI does, at the price of running the infrastructure yourself. Relevance AI is the managed answer, with agent governance, approvals, evals, and observability built rather than assembled. If you have engineering capacity and want to avoid metered pricing, n8n almost always wins on cost. If you want business users authoring agents with guardrails, n8n will not get you there without significant internal work.

Choose n8n if

Technical or semi-technical teams building long, multi-step automations, enrichment waterfalls, AI agents, and internal integrations, who want per-execution economics in the cloud or full data control self-hosted, and who are comfortable reading JSON when something breaks.

Choose Relevance AI if

Revenue and operations teams that want AI agents doing repeatable research, enrichment, outreach, and triage work under supervision, and that have someone willing to treat agent building as an ongoing job rather than a one-week setup. Strongest where the work is judgment-heavy and unstructured, which is exactly where a rules-based automation tool stalls.

Side by side

13 attributes

Attribute	n8n	Relevance AI
Category	GTM Engineering	GTM Engineering
Starting price	About $24/mo (Cloud Starter, 2,500 executions; roughly $20 on annual billing) (free plan available)	Free (200 Actions per month); Pro from $19 per month billed annually (free plan available)
Pricing model	Two paths. Cloud: subscription tiers metered by workflow executions per month (a run is one execution regardless of step count), with unlimited workflows and steps on every tier. Self-hosted: the Community edition is free under the fair-code Sustainable Use License, with paid Business and Enterprise self-hosted tiers adding collaboration, SSO, environments, and support. Prices are quoted in euros; dollar figures shift slightly with exchange rates.	Two meters plus a plan fee. Actions are consumed one per tool run, including runs that fail or retry. Vendor Credits cover the underlying LLM and third-party model spend, passed through at wholesale with no markup, and can be bypassed entirely on paid plans by connecting your own OpenAI or Anthropic API keys. Plans set the included Actions, included Vendor Credits, number of build users, and number of projects. This structure took effect on 8 September 2025 and replaced the previous single-credit model; the Business plan was discontinued at the same time.
Free plan	Self-hosted Community edition is free and unmetered on your own infrastructure	200 Actions per month, a one-time grant of 1,000 Vendor Credits, one build user, one project
Free trial	Cloud trial, no card required	No time-limited trial; the free plan serves that purpose
Best for	Technical or semi-technical teams building long, multi-step automations, enrichment waterfalls, AI agents, and internal integrations, who want per-execution economics in the cloud or full data control self-hosted, and who are comfortable reading JSON when something breaks.	Revenue and operations teams that want AI agents doing repeatable research, enrichment, outreach, and triage work under supervision, and that have someone willing to treat agent building as an ongoing job rather than a one-week setup. Strongest where the work is judgment-heavy and unstructured, which is exactly where a rules-based automation tool stalls.
Setup time	Cloud: minutes to sign up, and a first webhook-to-Slack workflow the same hour. Self-hosted: a Docker one-liner for a test instance; a hardened production deployment with backups and HTTPS is a half-day for someone who has run containers before.	An hour to sign up, clone a marketplace agent, and see it run. A week or two to get a first agent doing real work against real data, most of which is spent writing instructions, connecting integrations, and discovering the edge cases where the agent is confidently wrong.
Learning curve	Steeper than task-based tools: expect a few days to internalize items, expressions, and node data mapping, typically via imported templates. Engineers acclimate almost immediately; operators without API experience need the templates and patience.	Low to begin, steep in the middle. The visual tool builder is approachable for a non-engineer, but reliable agents require prompt discipline, structured output enforcement, and an appetite for reading traces. Multi-agent Workforces and custom API steps are a genuine technical exercise, not a no-code one.
Platforms	Web app (cloud), Self-hosted (Docker, npm), Embedded (commercial license), REST API	Web application, REST API, Model Context Protocol (MCP) server, Slack, Microsoft Teams, Android app, Embeddable tools and agents
Compliance	SOC 2, GDPR	SOC 2 Type II, GDPR
Founded	2019	2020
Headquarters	Berlin, Germany	Sydney, Australia
Ownership	Venture-backed, founder-led	Independent, venture-backed (OnSearch Pty Ltd trading as Relevance AI)

Strengths and limitations

n8n

Strengths

Per-execution pricing inverts the category's cost model; long, complex workflows, exactly the kind GTM engineering produces, are where it is cheapest relative to rivals.
Free self-hosted Community edition provides a permanent exit ramp and full data sovereignty, a structural negotiating position no closed rival offers.
Code nodes and the HTTP Request node remove the capability ceiling; if an API exists, n8n can drive it without leaving the canvas.
LangChain-based agent nodes made it one of the fastest paths from 'AI idea' to 'AI in production', with approvals, retries, and logging around the model.

Limitations

The learning curve is real: items, expressions, and JSON structure confront you in week one, and non-technical users often stall where Zapier would have carried them.
The integration catalog (400+) is an order of magnitude smaller than Zapier's; long-tail SaaS tools frequently mean building against the raw API via the HTTP node.
Fair-code is not open source by OSI definition, which complicates some corporate policies and community expectations, and the license debate resurfaces periodically.
Cloud Starter's 2,500 executions can pinch for high-frequency polling triggers; trigger design (webhooks over polling) becomes a cost skill.

Relevance AI

Strengths

The agent abstraction is genuinely well built: instructions, scoped tools, knowledge, approval gates, and escalation rules are all first-class rather than bolted on.
Tracing and cost visibility are better than most competitors, showing per-step model calls and per-run cost, which turns debugging from guesswork into reading a log.
The two-meter pricing separates platform cost from model cost honestly, and bring-your-own-keys removes the markup that most agent platforms quietly charge.
Approval gates and escalation are the right primitives for letting an agent touch a CRM or an inbox without an incident.

Limitations

Cost is hard to forecast. Actions are charged per tool run including failures and retries, and a multi-agent Workforce fans out into far more runs than a first-time buyer estimates.
The public pricing page shows only Enterprise as of August 2026; Free, Pro, and Team still exist but you have to dig through documentation to find their terms, which is a deliberate move away from self-serve buyers.
The Pro to Team step is punishing, roughly $19 to $234 per month for under three times the Actions, and there is no longer a Business tier in between since it was retired in September 2025.
Governance essentials are Enterprise-gated: evals, agent performance observability, audit logs, SSO, RBAC, and Salesforce, Snowflake, and Zendesk triggers are all out of reach of a self-serve buyer.

Pricing compared

n8n

Two paths. Cloud: subscription tiers metered by workflow executions per month (a run is one execution regardless of step count), with unlimited workflows and steps on every tier. Self-hosted: the Community edition is free under the fair-code Sustainable Use License, with paid Business and Enterprise self-hosted tiers adding collaboration, SSO, environments, and support. Prices are quoted in euros; dollar figures shift slightly with exchange rates.

Community (self-hosted)Free
Starter (Cloud)~€20 to €24
Pro (Cloud)~€50 to €60
Business / EnterpriseCustom

For long workflows, nothing in the category touches n8n's economics: the per-execution meter makes a 40-step enrichment waterfall cost the same as a 2-step alert, and the same pipeline on task or operation pricing can cost ten to fifty times more at identical volume. Against that, the true cost is skill: n8n assumes you can read JSON, debug an HTTP call, and occasionally write a line of code. Teams with that skill get Zapier-class capability at a fraction of the spend, plus a free self-hosted exit ramp that caps vendor risk permanently. Teams without it will burn the savings in time.

Relevance AI

Two meters plus a plan fee. Actions are consumed one per tool run, including runs that fail or retry. Vendor Credits cover the underlying LLM and third-party model spend, passed through at wholesale with no markup, and can be bypassed entirely on paid plans by connecting your own OpenAI or Anthropic API keys. Plans set the included Actions, included Vendor Credits, number of build users, and number of projects. This structure took effect on 8 September 2025 and replaced the previous single-credit model; the Business plan was discontinued at the same time.

Free$0
Pro$19
Team$234
EnterpriseCustom

Priced against what it replaces, the Pro plan is cheap: $19 a month plus metered model spend for work that would otherwise be a contractor's afternoon. The problem is the shape of the curve above it. Team at $234 a month gives under three times the Actions for more than ten times the price, and the governance features that make agents safe to leave running (evals, observability, audit logs, SSO) are not purchasable at any published price. A small business gets real value from the free and Pro tiers for supervised, human-in-the-loop work. A company that wants agents operating unattended on customer data is buying Enterprise, and should assume a five-figure annual commitment and a procurement cycle.

Editorial verdict on each

n8n

Momentum

n8n is what the automation category looks like when it is priced and licensed in the buyer's favor: pay per run instead of per step, read the source, and leave for your own server whenever you like. For the GTM engineer building long enrichment waterfalls and AI-agent workflows, those three facts compound into the category's best deal, and the LangChain-native agent tooling has made it the default engine of the DIY stack. The honest cost is skill: it asks more of you in week one than Zapier ever will, and its integration catalog still leans on the HTTP node for the long tail. Teams with a technical operator should default here; teams without one should pay the Zapier tax knowingly.

Read the full n8n profile

Relevance AI

Relevance AI is one of the better-engineered agent platforms available to a small company, and the parts that matter most for production use, tracing with per-step cost, approval gates, escalation rules, a job queue with retries, and an honest two-meter bill, are more mature here than in most of its peers. The friction is commercial rather than technical. Pricing jumps from $19 to $234 per month with under three times the Actions, the Business tier that used to bridge that gap was retired in September 2025, and the governance features that make agents safe to leave running unattended (evals, observability, audit logs, SSO) are all locked behind a quote-only Enterprise plan. The public pricing page now advertises nothing else, which tells you where the company's attention has gone. Buy the Free or Pro plan for supervised, human-in-the-loop work where a person reviews output, and expect real value from it. Do not plan an unattended, customer-data-touching deployment on a self-serve plan, because the tools to prove it is behaving are not sold at that price.

Read the full Relevance AI profile

n8n profile last reviewed 2026-08-22; Relevance AI last reviewed 2026-08-23. Pricing is compiled from public sources and can change without notice. See our methodology.