Zapier vs Make vs n8n (and AI Agent Builders): Choosing an Automation Platform

Automation platforms connect the apps you already use so that work happens without copy and paste: a form submission becomes a CRM record, an invoice triggers a Slack message, a new file gets summarized and filed. For years the choice was mostly Zapier versus Make, with n8n as the option for technical teams. Now every platform offers AI steps and “agents”, and a new group of AI-first tools promises assistants that decide what to do on their own.

This guide is for operations managers, founders, marketers and technical teams choosing where to build their automations. The central decision has two parts. First, which classic workflow platform fits your skills and budget: Zapier, Make or n8n. Second, whether you need an AI agent at all, or whether a predictable workflow with one AI step would do the job more cheaply and reliably.

What actually matters when choosing

• How you’re billed. Platforms meter different things: Zapier counts tasks, Make counts credits (historically “operations”), and n8n counts workflow executions. The same automation can cost very different amounts depending on the model.
• Ease of use versus flexibility. Linear, form-driven builders are quick to learn. Visual canvases with branching, loops and code steps handle more complex logic but take longer to master.
• Integration coverage. Check that the specific apps you rely on, and the specific triggers and actions you need, are supported. A large headline number doesn’t guarantee your niche tool is covered well.
• Hosting and data control. Some organizations need automations to run on their own servers for compliance or cost reasons. Only some platforms allow that.
• Reliability and predictability. Deterministic workflows do the same thing every time. AI agents make decisions, which is useful for messy tasks but harder to test and audit.
• Who will maintain it. An automation built by one enthusiast can become a hidden dependency. Choose a tool the rest of the team can understand.

Understanding the pricing models

Before comparing plans, it helps to understand what each unit means.

• Tasks (Zapier). Broadly, each successful action step counts as a task. A workflow with one trigger and four actions that runs 100 times uses around 400 tasks. Long, multi-step workflows consume tasks quickly.
• Credits (Make). Each module that runs in a scenario generally consumes credits, and heavier steps such as AI modules can consume more. Make’s per-unit cost is typically lower, but checks and filters count too, so frequent polling adds up.
• Executions (n8n). One execution is one full run of a workflow, regardless of how many steps it contains. That makes long, complex workflows comparatively cheap, while very frequent short runs (say, every minute) use executions fast. Self-hosting the Community Edition removes the platform fee entirely, though you pay for and maintain the server.

The practical lesson: estimate how many times each workflow runs per month and how many steps it has, then price it on each platform. A five-step workflow that runs 1,000 times is a very different bill under per-step and per-run models.

The main options

Pricing below reflects published plans as of September 2026. Automation pricing changes frequently and often depends on usage tiers, so confirm current pricing and limits on each vendor’s site.

Zapier

Zapier is a no-code automation platform connecting 8,000+ apps, with Zaps (its workflows), AI agents and Tables for storing data. It’s the best-known name in the category and usually the easiest place for a non-technical user to start.

Its strengths are breadth of integrations and a simple, step-by-step builder that most people can pick up in an afternoon. The main limitation is cost at scale: because every action step counts as a task, busy multi-step workflows can become expensive, and the free plan’s 100 tasks per month is only enough for light personal use. Very complex logic is possible but can feel less natural than on a visual canvas.

Pricing snapshot: Free plan (100 tasks/mo); Professional from ~$19.99/mo annual ($29.99 monthly); Team $69/mo annual.

Best for: Non-technical teams who want to connect popular apps quickly and value simplicity over cost per step.

Make

Make is a visual no-code automation platform with AI agents, connecting 3,000+ apps. Workflows, called scenarios, are built on a canvas where you can see data flow between modules, with routers for branching and tools for iterating over lists.

Make suits people who think visually and need more complex logic than a linear flow, and it’s generally cheaper per step than Zapier. The trade-offs: the canvas and data-mapping concepts take longer to learn, it supports fewer apps than Zapier, and because modules consume credits even when a scheduled check finds nothing, poorly designed scenarios can waste credits.

Pricing snapshot: Free plan (1,000 credits/mo); Make plan from $9/mo.

Best for: Ops-minded users building branching, multi-step workflows who want more capacity for the money.

n8n

n8n is a fair-code workflow automation and AI agent builder, available as a cloud service or self-hosted. Its visual editor supports code steps in JavaScript or Python, and it has become a popular choice for building AI agent workflows.

Its standout feature is the free self-hosted Community Edition: technical teams can run n8n on their own servers, keeping data in-house and avoiding per-run fees. On the cloud plans, pricing per workflow execution favors long, complex workflows. The limitations: it’s more technical than Zapier or Make, self-hosting means you’re responsible for updates, security, backups and uptime, and its library of prebuilt integrations is smaller than Zapier’s, so you’ll use generic HTTP requests more often. Its fair-code license also carries restrictions that matter if you plan to build a commercial product on top of it.

Pricing snapshot: Free self-hosted Community Edition + cloud free trial; Cloud Starter from €20/mo.

Best for: Technical teams who want control over hosting and data, or who run complex workflows at volume.

Pipedream

Pipedream is a developer-focused integration and workflow platform with code steps, 2,500+ APIs and MCP servers. It sits between no-code builders and writing your own integration code.

For developers, it’s a fast way to glue APIs together with real code where needed, without managing servers. It’s not a good fit for non-technical users, who will find Zapier or Make much more approachable.

Pricing snapshot: Free plan (10K invocations/mo); Advanced $29/mo; Business $99/mo.

Best for: Developers who want hosted, code-friendly workflows.

Gumloop

Gumloop is a no-code AI automation platform for building AI-powered workflows and agents. It’s built around AI steps from the start: processing documents, scraping and summarizing web pages, classifying data and passing results onward.

It suits teams whose automations are mostly about AI processing rather than simply moving data between apps. The limitation is that for straightforward “when X happens, do Y” integrations, a classic platform is usually simpler and has broader app coverage.

Pricing snapshot: Free plan / 14-day trial; paid from $37/mo.

Best for: Marketing, research and ops teams building AI-heavy workflows without code.

Lindy

Lindy is an AI assistant and agent platform focused on everyday work tasks: email, meetings, CRM updates and similar. Rather than designing a workflow step by step, you configure an assistant to handle a category of work.

This can be appealing for busy professionals who want help triaging email or preparing meeting follow-ups. The trade-off is less predictability than a fixed workflow. Agents interpret instructions, so they need clear guidelines, sensible permissions and human review for anything sent to customers. Per-user pricing also adds up across a team.

Pricing snapshot: Free trial; paid from $29.99/mo per user.

Best for: Individuals and small teams who want an AI assistant for inbox, calendar and CRM tasks.

Relevance AI

Relevance AI is a platform for building and deploying AI agents and multi-agent “AI workforces” without code. It targets business functions such as sales and support, where several agents might research, draft and route work.

It’s worth considering if your organization is deliberately investing in agent-based processes and has someone to design, monitor and refine them. For most small teams, it’s more than they need, and a classic automation with an AI step will be cheaper and easier to trust.

Pricing snapshot: Free plan (200 actions/mo); Pro from $19/mo annual ($29 monthly).

Best for: Teams building structured, multi-agent processes for sales or support.

Also worth knowing: Dify is an open-source platform for building LLM apps and RAG pipelines that technical teams can self-host.

Side-by-side

Tool	Best for	Free plan	Starting price	Main trade-off
Zapier	Simple app-to-app automation	Yes (100 tasks/mo)	From $19.99/mo	Per-task billing gets expensive at scale
Make	Complex visual workflows on a budget	Yes (1,000 credits/mo)	From $9/mo	Steeper learning curve than Zapier
n8n	Self-hosting and complex workflows	Yes (self-hosted)	From €20/mo	More technical; self-hosting needs upkeep
Pipedream	Developers gluing APIs with code	Yes (10K invocations/mo)	From $29/mo	Not suited to non-coders
Gumloop	AI-heavy no-code workflows	Yes (free plan/trial)	From $37/mo	Overkill for simple integrations
Lindy	AI assistant for email and meetings	Free trial	From $29.99/mo	Less predictable than fixed workflows
Relevance AI	Multi-agent business processes	Yes (200 actions/mo)	From $19/mo	Needs design and monitoring effort

When an AI agent is overkill

AI agents are useful when a task involves judgement over messy input: reading varied emails, researching a lead across sources, deciding which of several actions to take. They are overkill when:

• The rule is clear. “When a Typeform is submitted, add a row to the sheet and notify the channel” doesn’t need an agent. A standard workflow is cheaper and does exactly the same thing every time.
• You only need one AI step. Summarizing a document or categorizing a ticket can be a single AI action inside a Zapier, Make or n8n workflow. You keep the predictability of a workflow with a small amount of AI where it helps.
• Mistakes are costly. Sending invoices, changing customer records or emailing clients benefits from deterministic logic, or at least an approval step before anything goes out.
• Nobody will monitor it. Agents need someone to check outputs, refine instructions and handle edge cases. Without that, errors accumulate quietly.

A good rule of thumb: start with a workflow, add AI steps where the input is unstructured, and move to an agent only when the branching logic becomes too complex to express as rules.

How to decide

You’re a non-technical team connecting a handful of popular apps. Start with Zapier. Its free plan is enough to test a workflow or two, and its integration coverage is the broadest. Our Make vs Zapier comparison explains when switching makes sense.

Your workflows are getting long and your Zapier bill is climbing. Price the same workflows on Make, which charges less per step, or n8n Cloud, which charges per run. See n8n vs Zapier for the trade-offs.

You have developers and care about data control. Self-host n8n’s Community Edition, or compare it with Make in Make vs n8n. Budget time for maintenance and security updates. If your team prefers writing code, Pipedream is another option.

You’re a solo operator with a few light automations. The free plans of Zapier or Make may be all you need. Don’t pay for an agent platform to move data between two apps.

You want an assistant to handle email and meeting follow-ups. Try Lindy on a free trial, starting with drafts you review before anything is sent. Gumloop vs Lindy covers how a workflow-first AI tool differs from an assistant-first one.

You’re building AI-driven processes for a sales or support team. Gumloop for AI workflows, Relevance AI for multi-agent setups. Assign an owner to monitor results before scaling.

Common mistakes to avoid

• Comparing headline prices instead of real usage. Count runs and steps per workflow, then price them under each billing model.
• Using an agent where a rule would do. It’s more expensive, less predictable and harder to debug.
• Self-hosting without a plan for maintenance. Free software still needs updates, backups and monitoring.
• Letting one person own every automation. Document what each workflow does so the team isn’t stuck when that person leaves.
• Giving AI tools broad permissions from day one. Start with read-only access or approval steps, then widen access as you gain confidence.

FAQ

Is Zapier or Make cheaper?

For multi-step workflows, Make is usually cheaper per step. Zapier can still be the better value if its ease of use saves your team significant time, or if you need an integration Make doesn’t support.

Is n8n really free?

The self-hosted Community Edition has no license fee, but you pay for your server and the time spent maintaining it. n8n Cloud is paid after the free trial.

Do I need an AI agent platform, or can Zapier, Make and n8n handle AI?

All three offer AI steps and agent features. For most teams, adding an AI step to a regular workflow is enough. Dedicated agent platforms make sense for complex, judgement-heavy processes.

Which platform has the most integrations?

Based on published figures, Zapier lists 8,000+ apps, Make 3,000+ and Pipedream 2,500+ APIs. Check your specific apps and the actions you need rather than relying on totals.

The bottom line

Zapier remains the easiest starting point and the widest integration library, at a higher cost per step. Make offers more capacity and more flexible logic for the money if you’re willing to learn its canvas. n8n is the strongest option for technical teams who want to self-host or run complex workflows at volume.

AI agent builders like Gumloop, Lindy and Relevance AI are useful for judgement-heavy work, but many teams will get most of the value from a classic workflow with a well-placed AI step. Start simple, measure, and add autonomy only where it clearly pays off. Browse the full automation and agents category for more options.