Make

This Make.com review covers what Make is used for, its key features, the credit-based pricing plans and their real costs, how Make compares with Zapier and n8n, and whether it is worth paying for. Make started in Prague as Integromat, was acquired by the process-mining company Celonis in 2020 and was renamed Make in February 2022 (Wikipedia). It is a visual automation platform: you build a scenario on a canvas by linking modules, and every module is one action in one app. The pricing page lists 3,500+ apps, an HTTP module for any API without a native connector, and AI agent tools on top. Among automation tools, Make is cheaper than Zapier for most multi step workflows and more visual than n8n, but it has a steeper learning curve than simple trigger-action tools and its credit meter needs watching.

What is Make used for?

Make is used to automate work that moves data between apps. A scenario starts with a trigger module (a form submission, a new row, a webhook, a schedule) and then runs any number of actions: create a CRM record, post to Slack, update Google Sheets, send an invoice, call an AI model. You can build automations that run on a schedule, react to a webhook or chain multiple tools in one scenario. Typical automated workflows are lead routing from forms to a CRM, order syncs between a shop and an accounting tool, content pipelines that draft posts with an AI provider, reporting jobs that pull data from many tools into one sheet, and internal approvals with branching logic.

Small businesses use Make as their main no code automation platform. Agencies and operations teams use it for complex workflows that Zapier makes expensive. Technical teams use it as a middle ground between point-and-click tools and code: the HTTP module, webhooks, data stores and custom variables cover most cases where a native connector is missing. An HTTP call to an internal API or to AI services without a connector is one module like any other. Make also runs AI agents: an agent picks which of your scenarios and tools to call from an instruction, instead of following one fixed path.

Key features

• Visual scenario builder: a canvas where each module is a step and the data flow is visible. The visual builder shows how many bundles passed through each module on every scenario run, which makes debugging easier than in a list-based workflow builder.
• Routers, filters and iterators: routers split a scenario into different paths, filters decide which path runs, and iterators and aggregators handle lists. This is real branching logic and conditional logic on the canvas, available on the free plan. Core and up allow unlimited active scenarios; the free plan limits how many run at once.
• Error handling: error handling is built into the canvas. Error handler modules (Rollback, Break, Resume, Commit, Ignore) let a scenario recover instead of stopping. Make does not count credits for them.
• Apps and the HTTP module: 3,500+ apps with native connectors, plus an HTTP module and webhooks to call any REST API. Custom apps let you package an internal API as your own connector.
• AI agents and the AI toolkit: agents and AI modules on the same canvas (see below).
• Data stores and custom variables: small built-in tables for state between runs, and variables shared across scenarios (custom variables start on the Pro plan).
• Scheduling: runs on a schedule, on a webhook or on demand. The free plan has a 15-minute minimum interval; paid plans schedule down to the minute.
• Advanced features for builders: the Make API has more than 300 REST API endpoints to manage scenarios and the platform itself, from the Core plan up.
• Teams and governance: team roles, shared scenario templates, and on Enterprise advanced security features, custom functions and enterprise app integrations such as Workday, ServiceNow and Coupa.

Make pricing

Make's pricing model has five pricing plans: Free, Core, Pro, Teams and Enterprise. The billing unit is the credit. Most module actions use one credit; routers and error handlers use none; modules that use Make's AI provider can use more, based on tokens. If you connect your own key for an AI service, the module uses one credit per operation and you pay the AI provider directly for tokens. Credits replaced "operations" as the billing unit on August 27, 2025; a non-AI operation still costs one credit (Make Help Center). Prices on the Make pricing page, checked October 14, 2026, at 10,000 credits a month:

• Free: $0. 1,000 credits a month, the no-code visual workflow builder, 3,500+ apps, routers and filters, a 15-minute minimum interval between runs.
• Core: $9 a month billed annually ($10.54 billed monthly). Unlimited active scenarios, scheduling down to the minute, more data transfer and access to the Make API.
• Pro: $16 a month billed annually ($18.73 billed monthly). Priority scenario execution, custom variables and full-text execution log search.
• Teams: $29 a month billed annually ($33.96 billed monthly). Teams and team roles, and shared scenario templates.
• Enterprise: custom pricing. Custom functions, enterprise app integrations, 24/7 enterprise support, overage protection, advanced security and a Value Engineering team.

Paid plans start at 10,000 credits and scale up with a slider; the plan price rises with the credit volume, and annual billing is about 15% cheaper than monthly. The lower plans differ mostly in scheduling and team features, not in the apps you can use: there are no premium apps that only higher pricing plans unlock, apart from the enterprise app integrations. Extra credits come in bundles of 1,000 or 10,000 at your plan's rate, and Core, Pro and Teams can auto-buy 10,000 credits before they run out. Make also has a Start-up Plan for companies with fewer than 20 employees and discounts for non-profits.

The real costs to check: credits expire at the end of the term, so unused credits do not roll over. Each module in a scenario run uses credits, so one run of a ten-step scenario costs about ten credits, and a scenario that loops over 100 items costs one credit per module per item. A polling trigger that checks every minute uses a credit on every check, even when there is no new data. If credits run out, scenarios stop until you buy more. Data storage and data transfer allowances also scale with credits (10 MB of storage and 5 GB of transfer per 10,000 credits).

AI agents and advanced features in Make

Make AI Agents run inside your scenarios and decide the next step themselves. You give an agent a goal, a set of tools (your other scenarios and modules) and an AI model, and it chooses which tool to call and in which order. That fits work where the path changes per case, such as triaging support emails or enriching leads. A fixed scenario is still cheaper and easier to test when the steps are always the same.

AI modules run in two ways. With Make's AI provider you need no account at an AI company, and credits follow token use. With your own key for OpenAI, Anthropic Claude or another provider, each module action is one credit and the tokens are billed by that provider. For high volume, your own key is usually the cheaper and more predictable option. Make's AI toolkit modules cover common jobs such as summarising, classifying and extracting data, and the HTTP module reaches any other AI service with an API.

Make vs Zapier: which is more cost effective?

Make is a competitor of Zapier and is usually cheaper for multi step workflows. Both bill per action: Zapier counts a task for each action step in a Zap, and Make counts a credit for each module action. The difference is the plan price per action, and that Make's routers and error handlers are free and part of every plan. Zapier's paths based branching and some multi step zaps features sit on higher plans. Zapier has more native integrations and a simpler editor for non technical users; Make's visual builder handles complex scenario logic, iterations and data mapping better. Zapier's own comparison page argues that Zapier is more reliable and easier (Zapier, competitor-written); for a team that builds complex workflows, Make's canvas is the stronger tool. For one-step automations between two popular apps, Zapier is quicker to set up, and a visual workflow builder adds little when one scenario has only two steps.

Make vs n8n for technical teams

n8n is the main alternative for technical teams. It is open source and you can self host it, which removes per-credit costs at high volume; you pay for your own server and maintenance instead. n8n also allows code steps in JavaScript and Python inside a workflow. Make is fully hosted, has many more native connectors and is easier for non-developers. Make has no self hosted options. If your team wants to self host, keep data on its own infrastructure or run very high volume, n8n is often more cost effective; if you want a managed service with a visual canvas and less setup, Make is the better fit.

Where Make shines — and where it falls short

Strengths:

• The visual scenario builder makes complex workflows readable and easy to debug.
• Routers, filters, iterators and error handling are included on every plan, including the free plan.
• Usually cheaper than Zapier per action, with a free plan of 1,000 credits a month.
• 3,500+ apps, an HTTP module for any API, and AI agents with your own key or Make's AI provider.
• A clear execution history for every scenario run.

Trade-offs:

• A steeper learning curve than trigger-action tools; mapping bundles and arrays takes practice.
• Credits burn faster than newcomers expect: every module, every item in a loop and every polling check counts.
• Unused credits expire at the end of the term.
• AI modules through Make's AI provider can use more than one credit per action.
• No self-hosted version, and 24/7 support is an Enterprise feature.

How Make compares

• Zapier: the largest app library and the simplest editor; usually more expensive for multi-step automations.
• n8n: open source, self-hostable and code-friendly; more setup and maintenance.
• Pipedream: developer-first workflows with code steps in Node.js and Python.
• Workato: enterprise integration and automation with governance features, at enterprise prices.
• Microsoft Power Automate: the natural choice inside Microsoft 365, with desktop RPA.
• Tray.io: an integration platform for larger technical teams.
• IFTTT: simple personal automations between consumer apps and devices.
• UiPath: robotic process automation for desktop and legacy systems without an API.

Is Make worth it?

Make is worth it when your automations have several steps, branches or loops, and you want a hosted tool that stays cheaper than Zapier at volume. The free plan is enough to build and test real scenarios, the Core plan at $9 a month billed annually covers most small businesses, and the Pro plan adds the advanced features (custom variables, priority execution) that growing teams ask for. Which automation platform is the right alternative depends on how technical your team is. Make is a legitimate, long-running product owned by Celonis. It is less worth it for one-step automations between two apps, where Zapier is faster to set up, or for teams that must self host or run very high volume, where n8n is often cheaper. Budget for the learning curve and watch your credit usage in the first month. If you want help designing scenarios, migrating from Zapier or fixing a scenario that burns credits, post a project or browse the automation agencies and developers on LowCodeDevs.

Sources

• Make pricing: plans, prices, credits, usage allowance and FAQ (checked October 14, 2026).
• Make Help Center: credits: how credits work, AI provider usage and the switch from operations.
• Make Help Center: introducing credits: the change of billing unit.
• Make (platform), Wikipedia: history, Integromat and the Celonis acquisition.
• Zapier vs Make, Zapier: competitor-written comparison.
• Make.com review, AI Alleyway: hands-on review of credits and AI modules.
• Make pricing 2026, eesel AI: pricing walkthrough (written by a vendor of a competing product).
• Make alternatives, Lindy: alternatives list (competitor-written).