Use Zapier for simple rules between common apps, n8n when you need self-hosting or heavy branching at a flat execution price, and Relevance AI when an agent has to research, decide and draft. Pick one tool per workflow, not one tool for everything. Each fits a different layer of an AI operating system for a B2B team.

Key points

• Zapier bills by task, n8n bills by workflow execution, and Relevance AI sells its full feature set through an Enterprise plan priced by sales.

• n8n is the only one of the three you can run on your own servers, using its free Community edition.

• Zapier lists the most apps, at 9,000+, and in my experience has the gentlest learning curve for non-technical teams.

• Relevance AI is built around agents and multi-agent teams, so it fits tasks where the input changes every run.

• Decide per workflow: match the tool to how predictable the input is, how often it runs and where the data must live.

How do Relevance AI, n8n and Zapier compare side by side?

They overlap less than the marketing suggests. Zapier and n8n are workflow tools that added AI agent features, while Relevance AI started from agents and added workflow tools.

A disclosure first: I build client agents on Relevance AI, so I used each vendor's own pricing and docs pages for every figure below and checked them in October 2026.

The learning curve row is my judgment from building in all three, not a vendor claim.

What does each tool cost, and what do you pay per run?

Each tool counts usage differently, so compare the unit before the price. A cheap plan with the wrong unit can cost more than an expensive one.

Zapier: priced per task

According to Zapier's pricing page, each successful action counts as one task. The Free plan includes 100 tasks a month, Professional starts at $19.99 a month and Team starts at $69 a month, with a task selector that runs up to 2M tasks a month.

Two AI details matter for GTM teams:

• MCP calls cost double. The page says "One MCP tool call uses two tasks from your Zapier plan's quota."

• Agents are billed separately. Zapier Agents use activities, not tasks. The free tier includes 400 activities a month and the Pro tier includes 1,500 for $400 billed annually.

n8n: priced per execution

n8n's pricing page states that "Pricing is based on monthly workflow executions, regardless of complexity." Starter is 20€ a month for 2.5K executions and Pro is 50€ a month for 10K, both billed annually. A Business plan sits at 667€ a month.

n8n's integrations directory lists 2,000+ integrations, including an HTTP Request integration.

That unit matters. A 20-step workflow costs one execution on n8n but can use 20 tasks on Zapier, so long workflows tilt toward n8n.

Relevance AI: priced through sales

The Relevance AI pricing page I checked shows one plan, Enterprise, with a "Talk to sales" button. It lists "Unlimited Agents & Tools," "Unlimited Workforces," "Custom Actions" and "Custom Vendor Credits." Budget for a sales conversation before you can compare it line by line.

Whatever the pricing unit, you are paying for the same shift: from disconnected tools a person stitches together by hand to one orchestrated flow where signals move between systems on their own.

How do the AI agent features differ?

Relevance AI is agent-first, n8n gives you agent building blocks inside workflows, and Zapier offers agents as a separate product next to Zaps. The difference shows up in how much the model decides on its own.

The guide to AI operating systems vs AI agents covers the general split between rules and agents. Here is how each tool handles it.

Relevance AI

The pricing page describes the plan as "For companies looking to decouple growth from headcount via an AI Workforce." The product is organized around agents, the tools they call and Workforces, which are teams of agents passing work between them. The Enterprise list also includes agent evaluations and "RBAC & Audit Logs," which matter once several agents touch customer data.

n8n

n8n's advanced AI docs describe building "AI-powered workflows in n8n with LLM providers, agents, tools, memory, and MCP servers." You can combine models from providers such as OpenAI, Anthropic and Google in one workflow. The agent lives inside a visual workflow, so you can wrap it in fixed steps before and after.

Zapier

Zapier Agents run on their own plan, and the pricing page notes that "Zapier Agents can only take actions in the apps you've connected." Copilot, an automation assistant, is listed in beta. For most Zapier users, AI enters as a model step inside a standard Zap, which keeps the path fixed.

When does self-hosting matter for a GTM team?

Self-hosting matters when your security team says customer data cannot leave your own infrastructure, or when execution volume is high enough that a hosted plan gets expensive. For most GTM teams under 50 people, neither applies on day one.

n8n's hosting docs say "You can self-host n8n on your own infrastructure, on-premises, or in a private cloud," and "Without a license key, n8n runs as the free Community edition." The quickest install needs a Linux or macOS machine with curl, and production setups use Docker Compose.

Free software still costs time. Someone has to own:

• Updates. New versions, security patches and node changes.

• Uptime. If the server stops, every workflow stops with it.

• Credentials. API keys for the CRM, email and enrichment tools live on your box.

• Backups. Workflow definitions and execution logs need a copy somewhere else.

If nobody on the team would notice a stopped server within an hour, start on a hosted plan. Neither Zapier's nor Relevance AI's pricing page offers a self-hosted option, so a hard data-residency rule narrows the choice fast.

Which tool should run which workflow?

Pick the tool per workflow by asking three questions: does the input change shape, how many steps does it have and where must the data live. The answers point to one tool more often than not.

Run each workflow through these rules in order and stop at the first match:

1. Data must stay on your servers. Use self-hosted n8n.

2. The input is identical every time and the workflow has fewer than five steps. Use Zapier. Example: a demo request creates a CRM contact and posts in Slack.

3. The input is identical every time but the workflow has many steps or branches. Use n8n. Example: a weekly pipeline export that splits by region, enriches and writes to three sheets.

4. The input varies and the task needs reading, deciding and drafting. Use Relevance AI or another agent tool. Example: research an inbound company, match it to an offer and draft a reply for approval.

5. The task is a varied step inside a fixed process. Use n8n with an AI agent step, or a Zap with a model step. The fixed parts stay predictable and only one step uses a model.

What this looks like across a GTM team

These rows are illustrative, not client stories. Running two or three tools is normal once each one has a clear job.

How do you connect agents to the rest of your stack?

Through a tool layer that handles authentication for each app, so every agent does not hold its own copy of your API keys. This is where most agent builds get messy.

Composio is one option I build on. Its docs describe giving "agents tools, managed authentication, and secure execution across 1,600+ apps," with "OAuth, API keys, and tokens scoped to each user and refreshed automatically." It works with OpenAI, Anthropic and Vercel AI SDK, and offers a hosted MCP endpoint.

The point is permissions in one place. When five agents across two tools all need CRM access, a shared connection layer answers the question "who can write to the CRM?" with one list. The guide to rolling out Claude to a team securely covers setting those access rules before the agent count grows.

The tool matters less than what it reads. Every agent, in any of these tools, should read from and write to one shared context surface instead of its own private copy.

What else should you consider?

Gumloop is the one I would add to a shortlist if none of the three fits. It sits between Zapier's simplicity and an agent builder.

Gumloop's pricing page lists a Pro plan that "Starts at $37 / month" with 20k credits per month, plus a 14-day free trial. The page did not explain how credits are counted when I checked, so test a real workflow during the trial before you estimate monthly cost.

What are the common mistakes when picking an automation tool?

The most common mistake is choosing one tool for the whole company and forcing every workflow into it. The rest come from comparing sticker prices instead of usage units.

1. One tool for everything. Agent tools are a costly way to move a form fill, and Zapier is an awkward place for a 20-step branching report.

2. Comparing plan prices, not units. A task, an execution and a credit are different things. Price your three busiest workflows in each unit before you decide.

3. Self-hosting with no owner. A free Community edition with nobody watching it costs more than a hosted plan when it goes down during a launch.

4. Agents with no approval step. New agent workflows should start with a person approving every output before anything reaches a prospect.

5. Keys scattered across tools. Each tool holding its own CRM credentials makes access reviews painful. Centralize connections.

6. Picking the tool before the workflow. If you do not know which workflow costs the most, the tool choice is a guess.

How do you test a tool before you commit?

Build your single most expensive workflow in the shortlisted tool during its trial or free tier, then run it on real inputs for one week. A demo workflow tells you little.

Use this checklist during the test week:

• Usage. How many tasks, executions or credits did one week use? Multiply by 52.

• Failures. How many runs failed, and did the tool tell you clearly?

• Edits. How long did a non-technical teammate take to change one step?

• Review. Can a person approve a draft before it sends?

• Logs. Can you see what triggered each run and what it did?

• Access. Who on the team can see the stored credentials?

The L1 to L4 AI automation maturity ladder shows how much of a tested workflow you can safely hand off, and when to remove the review step.

What does this look like in dollars?

Here is the worked example from my AI Workflow Install page: a 12-person team where each person spends 8 hours a week on manual work, at a $60 loaded hourly rate. That is $299,520 a year, and in the example one workflow accounts for half of it, $149,760.

Against that number, the gap between a $20 and a $69 monthly plan barely registers. What matters is whether the tool fits the workflow well enough that it runs without constant fixes.

If that $149,760 workflow is rule-based, Zapier or n8n will cover most of it. If it involves reading and drafting, an agent tool with a review step fits better. The manual-work leak audit guide shows how to find that workflow in your own team before you open a single pricing page.

FAQ

Is n8n cheaper than Zapier?
For long workflows, often yes, because n8n counts one execution per run while Zapier counts each successful action as a task. For short workflows at low volume, Zapier's Free or Professional plan can cost less.

Can I self-host Zapier or Relevance AI?
Neither pricing page offers a self-hosted option. n8n is the one of the three with a free self-hosted Community edition.

Does Zapier have AI agents?
Yes. Zapier Agents run on a separate activity-based plan, with 400 activities a month free and 1,500 on the Pro tier.

Is Relevance AI only for large companies?
Its public pricing page shows an Enterprise plan priced through sales, so expect a sales conversation. Ask about entry options on that call.

Do I need Composio if my tool has native integrations?
Not always. A shared connection layer pays off when several agents across tools need the same app access with per-user permissions.

Should a small GTM team run more than one tool?
Yes, if each tool has one clear job. Two well-chosen tools beat one tool stretched across workflows it handles badly.

Find out which tool fits your first workflow

If you want help deciding which tool should run which workflow, book a free 30-minute Leak Call. We estimate what manual work in one area costs per year, and you get a costed workflow list within 48 hours. You can also see the tools I build on in my stack page.

About the author: Kevin Payne is an AI engineer and GTM operator who installs AI workflows for B2B teams. He has 10+ years in B2B SaaS demand generation and RevOps across Techstars, a16z and YC portfolio companies, and his writing has appeared in HubSpot, GetResponse, Outbrain and more.