Make.com

Make.com (formerly Integromat) is a visual workflow automation platform founded in Prague in 2012 and acquired by Celonis in 2020. It competes directly with Zapier but takes a more visual, more granular approach: scenarios play out on a canvas you can see and trace step by step, modules can pass data in complex ways without writing code, and the free plan is generous enough for real use. Make added native AI integrations in 2023, and by 2026 supports direct calls to OpenAI, Anthropic, Gemini, and others inside any workflow. Core plans start at $9 per month. Enterprise pricing is custom.

Make.com has been building workflow automation since before the category had a name. Founded in Prague in 2012 under the name Integromat, it spent a decade as the technically-minded European alternative to Zapier before a 2022 rebrand and a push into a larger market. By 2026 it sits as one of the two default answers when someone asks "what tool do I use to connect my apps," alongside Zapier, and it has built a distinct identity around a more visual, more granular approach to automation.

Quick verdict

Make is the right tool for users who want real control over their automation workflows without writing code. The visual canvas is its strongest differentiator: you can see the full scenario, trace every data path, and understand what's happening at each module without reading a log file. The free plan is genuinely useful, Core at $9 per month is one of the cheaper entry points among serious automation tools, and the AI integrations added in 2023 make it possible to put LLM calls directly inside a workflow.

It's not the right choice if you need self-hosting (Make is cloud-only), if you want to write custom code at arbitrary points in a workflow (look at n8n for that), or if you're building complex AI agent architectures rather than business process automation. But for connecting the apps your team uses daily and building workflows that include AI steps, Make covers a lot of ground.

The visual canvas

The core Make experience is the scenario builder. You open an infinite canvas, drag in modules for the apps you want to connect, and draw connections between them. Each module has inputs and outputs; you map data from one to another using a point-and-click interface that exposes every field the API returns. Where Zapier shows you steps in a linear list, Make shows you the full graph. On a simple two-module scenario that distinction doesn't matter much. On a scenario with routers sending data to five different paths depending on conditions, the graph view is significantly clearer.

This visual transparency is what makes Make particularly good for debugging. When a run fails, you can click on any module in the run history, see exactly what data went in and what came out (or what error was returned), and pinpoint the failure without reading through logs. It's not quite as powerful as n8n's per-step re-run capability, but for non-technical users it's a much more accessible debugging experience than Zapier's text-based history.

The canvas does get crowded. Complex scenarios with many modules and multiple routing paths start to look like a diagram someone gave up on. Make has tools to help, including notes and color coding, but there's no good answer to this problem at a certain scale. If your workflow logic is complex enough that the canvas feels unmanageable, it may be a signal that the work needs a different tool or a different architecture.

Data transformation without code

One of Make's genuine strengths is the depth of data transformation you can do at the mapping level without any code. When you're mapping an input field from one module to the output of another, Make exposes a formula system with functions for text manipulation, date formatting, number math, and array operations. You can concatenate strings, parse a date, extract part of a URL, run a regex, or perform conditional logic, all inside the mapping interface.

For users coming from Zapier, this is often a pleasant surprise. Zapier requires a separate "Formatter" step for many of these operations. In Make, the transformation happens inline at the point of mapping. That means fewer total modules, a cleaner canvas, and a more direct relationship between data and where it goes.

For users coming from n8n, the comparison is different. n8n lets you write actual JavaScript or Python at any step. Make's function system is powerful for its scope but not a substitute for real code. If you need to parse complex JSON, call a custom library, or run logic that doesn't fit Make's function vocabulary, you're blocked in a way you wouldn't be in n8n.

AI integrations in practice

Make added native AI modules in 2023 and they've grown into a real part of the platform by 2026. The OpenAI module, the Anthropic module, and the Google Gemini module all let you send a prompt (and optionally files, conversation history, or structured data) to an LLM and receive a response you can use in subsequent steps. The AI Scenario Builder generates a scenario from a text description, which is an imperfect but useful starting point for users who don't want to build from a blank canvas.

In practice this means you can build automations like: "When a new support ticket comes in via Zendesk, send the ticket to Claude with a classification prompt, then route it to the right team based on Claude's response." That kind of LLM-as-router pattern works well in Make because the branching after the AI module is where Make's routing tools shine. You get the LLM call, the conditional logic, and the downstream app actions all in one scenario you can see and trace.

What Make's AI integrations don't do is build genuine agent loops where the LLM plans and executes multiple steps autonomously. Make's scenarios are directed graphs that execute in a defined order. You can make them conditional and iterative, but the execution path is always something you've designed. For AI agent architectures where the model itself decides what tools to call, n8n or purpose-built agent platforms are a better fit. Make is better for "AI as one step in a larger business process" than for "AI as the orchestrator of an open-ended task."

Pricing breakdown

The Free plan is the most accessible starting point in the category. 1,000 operations per month and 2 active scenarios is real enough to automate a few personal or light business workflows. The 15-minute scheduling minimum means it's not suitable for near-real-time automation, but for tasks that run hourly or on triggers, the free tier works.

Core at $9 per month raises the operation count to 10,000 and lifts many of the Free plan's restrictions. This is the right tier for individuals or small teams with active automation needs. Pro at $16 per month adds faster scheduling (down to 1-minute intervals), increased data storage, and priority scenario execution. Teams at $29 per month adds multi-user collaboration with user management and team-level scenario sharing.

Operations-based pricing requires some upfront math. Before choosing a plan, map out how many modules your key scenarios have and how often they run. A scenario with 10 modules that runs 500 times per month costs 5,000 operations. That's well within the Core plan, but two or three such scenarios gets you close to the ceiling. Make's dashboard shows your consumption so you can track usage, but unexpected spikes can catch users off guard if their triggers fire more often than expected.

Enterprise pricing is custom and adds volume discounts, SSO, a dedicated customer success manager, and SLA guarantees. For teams at scale, the per-operation pricing on standard plans becomes expensive before you reach the Enterprise conversation.

How Make compares to the alternatives

Make vs Zapier Agents

These are the two most direct competitors in no-code workflow automation. Zapier has a larger US market share, a longer app library, and a reputation as the default choice. Make has a lower entry price, a more visual interface, and deeper data transformation at the module level. Zapier's linear builder is faster for simple two-step automations. Make's canvas is clearer on complex multi-path workflows. Zapier's AI features are growing but remain shallower than Make's current integration depth. At equivalent operation volumes, Make is usually cheaper. For users who've hit Zapier's limits on data manipulation or who want a clearer view of complex workflows, Make is worth evaluating directly.

Make vs n8n

n8n is for developers; Make is for everyone else. n8n lets you self-host, write real code, and build genuine AI agent loops. Make is cloud-only, codeless, and focused on business process automation rather than developer tooling. If your team includes engineers who want full control, n8n is the better tool. If your team is non-technical and wants a polished UI with 1,800+ ready-made integrations, Make handles more ground at a lower operational overhead. They're not really competing for the same user; the choice is usually clear once you know who will build and maintain the workflows.

Who Make is built for

Make's primary audience is the non-technical or semi-technical user who wants more depth than Zapier offers without stepping into developer tooling. Marketing operations professionals, e-commerce managers, operations coordinators, and small business owners are well-served by it. The visual canvas rewards users who think in flowcharts. The formula system in data mapping rewards users who've worked with spreadsheet functions and want similar power in automation.

Agencies managing automation for multiple clients find Make's team and organization features workable, though not as deep as purpose-built agency tooling. Anyone whose work involves connecting the standard SaaS apps and whose data transformation needs don't require code will find Make covers most of what they need.

The weakest fit is for developers wanting code flexibility, for teams needing to self-host for data privacy, and for anyone building AI agents rather than AI-augmented process automation. For those cases, n8n is the closer match.

Getting started

Make's onboarding steers you toward their template library, which is a reasonable starting point. Find a template close to what you want, open it, connect your accounts, and adjust the configuration. Most templates need modification but they give you the module structure to build from.

The AI Scenario Builder is worth trying even if the output needs editing. Describe what you want your scenario to do in plain language, let it generate a draft, then modify the modules it placed. It doesn't produce production-ready scenarios in most cases, but it's a faster starting point than building from scratch if you're new to the canvas.

For understanding the platform properly, Make's documentation is thorough and includes guided courses through their Make Academy. The community forums are active. If you're running into a specific integration problem, searching the community usually turns up a thread from someone who hit the same issue.

The free plan is large enough to evaluate the platform on real use cases before committing to a paid tier. Build two or three actual workflows you need, run them for a week, and see whether the operation limits and scheduling constraints fit your needs. That's a better evaluation than any demo.

Key features

• Visual scenario builder with drag-and-drop modules on an infinite canvas
• 1,800+ app integrations including Google, Slack, HubSpot, Shopify, Airtable, and more
• Native AI integrations with OpenAI, Anthropic Claude, Google Gemini, and others
• Data mapping and transformation with built-in functions, no code required
• Error handling and rollback support with automatic retry logic
• Scheduling from every 15 minutes (Free) up to every minute (Pro+)
• Advanced flow control: routers, aggregators, iterators, and filters
• Custom HTTP and REST API modules for any unlisted service

Pros and cons

Who is Make.com for?

• Marketing teams automating lead capture, CRM updates, and email sequences across tools
• E-commerce operators routing orders, inventory changes, and customer notifications
• Small businesses connecting the apps their teams use daily without hiring a developer
• Operations teams building multi-step approval workflows with conditional branching
• Agencies managing client automation scenarios across multiple connected accounts

Alternatives to Make.com

If Make.com isn't quite the right fit, the closest alternatives are zapier-agents , n8n , and gumloop . See our full Make.com alternatives page for side-by-side comparisons.