How to build an AI agent for your business: where to start with n8n or Make

What is an AI agent builder, and what does it do?

An AI agent builder is the platform you use to assemble the agent itself: a program that receives a goal in plain language, decides which steps to take, and then acts inside your software. It reads an inbox, pulls up a customer record, drafts a reply, opens a task. That last part is the dividing line with a chatbot. A chatbot answers, an agent executes. In a small company, an agent is almost always three pieces bolted together: a language model for the decision part, an automation platform for the connections to your business tools, and a set of rules that fence in what the agent is allowed to do. The two platforms covered here play that backbone role: n8n, rated 4.3 out of 5 by Stacknota, and Make, rated 4.1 out of 5.

How is an AI agent different from a regular automation?

A classic automation follows a fixed path: if this event happens, run that action. An agent adds a margin of decision, and that changes how the bill builds up. n8n charges for the full workflow execution rather than the step, so an agent that chains ten calls before it lands on an answer burns one execution out of the 2,500 included in the Starter plan. Make counts credits instead, and Stacknota notes that credit usage is hard to predict at high volume. That is the first thing to watch: an agent that deliberates a lot costs more than a straight-line scenario doing similar work. If you are still choosing between the big platforms, our comparison of Zapier, Make and n8n sets out the basics.

What can you actually build with n8n or Make?

Both tools cover the same ground: sorting and qualifying inbound requests, drafting replies, updating customer records, internal alerts, follow-ups. What differs is the technical guardrails. Make Core removes the cap on active scenarios, drops the run interval to one minute and accepts files up to 100 MB, against 5 MB and a 15-minute interval on the free plan. n8n Starter includes 2,300 AI credits per month, 5 concurrent executions, 1 shared project and unlimited users, which is a constant across every n8n plan. For real monitoring, Make Pro adds full-text log search, while n8n Pro opens up workflow history, global variables and 20 concurrent executions.

What does an AI agent cost on n8n or Make?

Two things matter before you read across those columns. The units are not the same: one n8n execution covers a whole workflow, one Make credit covers a scenario step. And at n8n, the higher tier of the Pro plan, at 50,000 executions, is listed at 145 euros per month. In our reading, the gap between Pro at 60 euros and Business at 800 euros monthly is not a volume gap at all: Business is what unlocks self-hosting, SAML and LDAP SSO, separate environments and Git version control. That is a change of nature, not a usage tier.

Where will your agent’s data be stored?

This is the criterion that separates the two most clearly. n8n scores 5 out of 5 on GDPR at Stacknota: cloud plans store data on servers in Frankfurt, Germany, with a pre-signed DPA available for download, an annual SOC 2 audit by an independent auditor and a public SOC 3 report. ISO 27001 is not mentioned. Self-hosted, the data sits wherever you install the tool. Make scores 4 out of 5: the infrastructure runs on AWS, EU server zones exist, but the exact physical location of eu1 and eu2 is not stated on the pages checked. Make does list SOC 2 Type II, SOC 3 and ISO 27001, with a DPA and a subprocessor list published in its contractual documents. For reference, Zapier hosts data in the United States with no EU option advertised, and drops to 2 out of 5 on this criterion.

How do you start without burning a month?

Start with a repetitive process whose rules you already know, and write those rules down before you open an editor. An agent does not clarify a fuzzy process, it executes it badly, faster. Then test on the free plans. Make has a permanent one, capped at 2 active scenarios and 1,000 credits per month, which is enough for a first agent. n8n has no cloud equivalent, only a trial with no credit card, but its self-hosted Community Edition is free: our article on what n8n actually costs sets out what that involves. Third step: limit what the agent is allowed to touch, read-only at the start. Fourth step: watch the logs. Make’s free plan keeps them for 7 days, which is short for spotting drift.

n8n or Make: which one fits your profile?

If nobody on the team is comfortable with a server, take Make. Its visual editor scores 4 out of 5 on ease of use against 3 out of 5 for n8n, and Core at $9 per month billed yearly is the lower entry price of the two. The caveats: no self-hosting, and credit usage you have to keep an eye on. The full Make writeup lists the limits plan by plan.

If you have a hard constraint on where data sits, a developer on hand, or a lot of users to onboard, take n8n. Unlimited users on every plan, billing per full execution and the Frankfurt cloud are what earn it 5 out of 5 on both features and GDPR. The caveats: a higher entry price at 20 euros per month billed yearly, and a steep step up to Business.

If you are sure of nothing yet, run the same agent on both free plans for a month, then look at which of your two mockups consumed more. That is the only measure that reflects your real volume, and no pricing table replaces it.