When automation comes up in a leadership meeting, the first question is rarely about features. On a recent call, an executive at a manufacturer asked us directly: are you working in environments we already have, or are you bringing a whole new platform we will have to staff and pay for? That is the right question, and it is the lens for the n8n vs Zapier vs Make decision. All three can move data between your systems. They differ on what you pay at volume, where your data lives, and who has to maintain the thing.
Here is how we walk mid-market teams through the choice, including why our own AI work runs on one of them.
Three Platforms, Three Pricing Models
The sticker prices look similar. The models behind them do not. Zapier bills per task, Make bills per operation, and n8n bills per workflow execution, meaning one full run counts once no matter how many steps it contains. As of mid-2026, Zapier’s Professional plan starts at $19.99 a month for 750 tasks, Make starts at $9 for 10,000 credits, and n8n Cloud starts around $20 for 2,500 executions, with the self-hosted edition free.
At low volume, any of them is affordable. The divergence shows up as workflows grow. At 10,000 tasks a month, Make runs roughly 70 percent cheaper than Zapier, and self-hosted n8n roughly 95 percent cheaper. A ten-step workflow that runs constantly is ten billable tasks per run in Zapier and one execution in n8n. If AI is in your plans, volume is in your future, because agent-style automations run all day. That math is a cousin of the consumption pricing we unpack in our explainer on AI costs, tokens, and credits.
Why Our AI Work Runs on n8n
We are opinionated here, and transparent about why. Nearly every client automation we build is orchestrated with n8n. It is open source, so there are zero licensing costs when self-hosted. It runs on a lightweight server, which means clients host it either on a small VM in their own Azure environment or on a local machine inside their firewall. Every one of our Microsoft-shop manufacturing clients has ended up doing exactly that.
The contrast that surprises IT leaders is with cloud-native automation stacks. Spinning up equivalent capability with native cloud services tends to auto-create a collection of resources that quietly bill every month. A single inexpensive server running an open platform keeps the cost visible and flat. Ongoing AI usage costs on top of that are typically modest, not thousands of dollars a month. And since n8n’s 2026 release added native LangChain integration and more than 70 AI nodes, it has become the strongest of the three for the agent workflows we build, the kind we describe in our guide to agent workflow automation.
The honest tradeoff: someone has to stand it up, secure it, and maintain it. n8n rewards teams with a technical partner or in-house engineering. It punishes teams that have neither.
When Zapier or Make Is the Right Call
Zapier earns its premium in one scenario: non-technical teams automating at low volume. With more than 9,000 app integrations and the most polished builder in the category, a marketer or office manager can connect tools in an afternoon with nobody from IT involved. If your whole automation footprint is a dozen simple workflows, pay for the ease and move on.
Make is the middle path. It delivers roughly ten times the operations per dollar of Zapier and a visual builder capable of genuinely complex logic, without requiring you to host anything. For a mid-market team with moderate technical comfort and growing volume, but no appetite for managing a server, Make is often the best value.
The Decision in Three Questions
Strip away the feature grids and the choice comes down to volume, data, and people. First, how many runs per month will you hit within a year? Under a few thousand, choose on ease. Above ten thousand, per-task pricing will hurt. Second, does your data need to stay inside your walls? n8n is the only one of the three you can fully self-host, which settles it for regulated or security-sensitive teams. Third, who maintains it? Be honest. The platform matters less than the operator, and an unmaintained automation fails silently until it fails loudly. Whichever way you lean, start by mapping the process itself, the discipline we cover in how to automate manual processes.
Our approach is to fit into what you already have rather than sell you a new platform, and to stand behind what we build after it ships. If you want help pressure-testing the choice against your actual workflows, start a conversation with our team.
Frequently Asked Questions
Which is cheapest: n8n vs Zapier vs Make?
At low volume the differences are small. At scale, Make is typically around 70 percent cheaper than Zapier, and self-hosted n8n approaches free on licensing, with costs limited to a small server and maintenance time.
Is n8n hard to set up for a mid-market company?
It requires a server and someone to secure and maintain it, either in-house or through a partner. In our client work it typically runs on a small VM in the client’s existing Azure environment or a local machine behind the firewall.
Which platform is best for AI automation?
n8n currently leads for AI agent workflows thanks to native LangChain support and a large library of AI nodes, plus the option to keep data on your own infrastructure. Zapier and Make both added AI agent features, which are fine for lighter use cases.
Can we use more than one of these platforms?
Yes, and some organizations do: Zapier for simple departmental automations and n8n or Make for high-volume or sensitive workflows. Just assign ownership, because ungoverned tools multiply quietly.
Let's work together.
Partner with Augusto to streamline your digital operations, improve scalability, and enhance user experience. Whether you're facing infrastructure challenges or looking to elevate your digital strategy, our team is ready to help.
Schedule a Consult
