Make.com (formerly Integromat) is the automation platform that turned "connect two apps" into a visual programming language. While Zapier made automation accessible and n8n made it self-hostable, Make carved out the middle ground: powerful enough for complex multi-branch workflows, visual enough that you don't need to write code, and priced aggressively enough that scaling doesn't bankrupt you.
We've been building and monitoring automations on Make for over a year. This review covers what it actually delivers in 2026 — including the credit math most reviews skip, the AI Agent features that just went GA, and the honest limitations you'll hit in your first month.
Quick Verdict
| Category | Rating | |---|---| | Ease of Use | ⭐⭐⭐⭐ (4/5) — Visual canvas is powerful but takes ~1 week to click | | Features | ⭐⭐⭐⭐⭐ (5/5) — Branching, routers, error handling, AI agents, HTTP module | | Pricing | ⭐⭐⭐⭐⭐ (4.5/5) — Significantly cheaper than Zapier at scale | | Integrations | ⭐⭐⭐⭐ (4.5/5) — 3,000+ apps plus HTTP module for anything with an API | | Support | ⭐⭐⭐ (3/5) — Slow on lower plans, community is strong | | Overall | ⭐⭐⭐⭐ (4.3/5) — Best visual automation platform for builders who need real logic |
Bottom line: If you've outgrown Zapier's linear workflows or you're tired of paying $50+/month for basic automations, Make is almost certainly the right move. If you're non-technical and need the absolute simplest tool, Zapier is still easier. If you're a developer who wants full code control, look at n8n.
What Is Make.com?
Make.com is a visual no-code automation platform that lets you connect apps, transform data, and build complex workflows using a drag-and-drop canvas. Think of it as the visual programming layer between your SaaS tools.
Founded in 2012 as Integromat (rebranded to Make in 2022), the platform has grown from a Zapier competitor into something fundamentally different. Where Zapier uses a linear "trigger → action" model, Make uses a visual canvas where you can branch, loop, filter, aggregate, and transform data in ways that would require actual code on other platforms.
In 2025–2026, Make pushed hard into AI territory. They launched Make AI Agents (now generally available), the Maia scenario-builder assistant, MCP (Model Context Protocol) support, native modules for OpenAI, Claude, and Gemini, and a built-in AI Toolkit that works without API keys on every plan. These aren't afterthought features — they're deeply integrated into the scenario builder.
The platform now supports over 3,000 app integrations natively, plus a generic HTTP module that can connect to literally any service with an API. That HTTP module is one of Make's secret weapons: if an app isn't in the directory, you can still automate it.
Key Features
Visual Scenario Builder
Make's canvas is the core experience and the main reason people switch from Zapier. Instead of a top-to-bottom list of steps, you get a visual flowchart where modules (individual actions) connect via paths that you can branch, merge, and loop.
The canvas supports:
- Routers — Split a single data stream into multiple paths based on conditions. A new lead comes in? Route enterprise leads to Salesforce, SMB leads to HubSpot, and spam to the trash — all in one scenario.
- Iterators and Aggregators — Loop through arrays of data (like line items in an invoice) and then aggregate results back into a single output. This is where Zapier users hit walls.
- Error handling routes — Attach dedicated error paths to any module. When a module fails, the error route catches it and can retry, send an alert, log the failure, or run a fallback. This is powerful but it's not automatic — you have to design these routes yourself.
- Filters — Place conditions between any two modules to control data flow without adding extra steps.
The visual approach has a genuine learning curve. Plan on spending about a week with it before the mental model clicks. Once it does, you'll build faster than on any linear platform. But that first week can be frustrating, especially if you're used to Zapier's step-by-step simplicity.
AI Agents and LLM Integration
Make's AI features in 2026 are legitimately impressive and go well beyond "we added a ChatGPT module."
Make AI Agents went generally available in mid-2026. These aren't just prompt-and-response modules — they're agentic workflows where an AI model can decide which tools to use, call multiple modules, and loop until a task is complete. As of June 2026, AI Agents support MCP (Model Context Protocol), meaning they can access tools exposed by external MCP servers alongside native Make modules in the same run.
The Make AI Toolkit is available on every plan (including free) and doesn't require your own API keys. You can prototype AI-powered scenarios immediately, then swap in native OpenAI, Anthropic Claude, or Azure OpenAI modules when you're ready to use your own keys for production workloads. Claude Sonnet 5 support was added in July 2026.
Maia is Make's built-in AI assistant that helps you design scenarios. Describe what you want to automate in plain language, and Maia generates a starting scenario. It's useful for getting a skeleton in place, though you'll always need to refine the output.
The catch: AI modules consume credits dynamically based on token usage, not a fixed amount per execution. A workflow that costs 5 credits today might cost 15 tomorrow if the input text is longer. This makes cost prediction for AI-heavy workflows genuinely difficult.
Data Transformation and Functions
Make treats data transformation as a first-class feature, not an afterthought. Every module output can be mapped, transformed, and combined using built-in functions before passing to the next step.
In May 2026, Make launched the Make Functions app — a new set of visual function modules for strings, math, arrays, dates, hash functions, and utilities that you can stack in sequence inside your scenario. Before this, you'd use inline formulas (which still work). The Functions app makes complex transformations more readable and debuggable.
The formula system supports:
- Text manipulation (replace, split, join, regex)
- Math operations
- Date/time parsing and formatting
- Array operations (map, filter, reduce, sort)
- JSON parsing and construction
- Base64 encoding/decoding
- Cryptographic hashing
For anyone who's tried to do a multi-step data transformation in Zapier using Formatter steps, Make's approach is night and day. You can do in one module what takes 3–4 Zapier steps.
HTTP Module and Webhooks
The HTTP module is arguably Make's most underrated feature. Any API endpoint — whether it's a niche CRM, an internal tool, or a brand-new SaaS product that hasn't built a Make integration yet — can be called directly.
You get full control over:
- HTTP method (GET, POST, PUT, DELETE, PATCH)
- Headers and authentication (OAuth2, API key, basic auth, custom)
- Request body (JSON, form data, multipart)
- Response parsing
Combined with webhooks (which let external services trigger Make scenarios), you can build integrations that don't exist anywhere else. This is the feature that makes Make viable for technical teams who need to integrate with internal APIs or less common tools.
The webhook trigger is instant — no polling delay. When an event hits your webhook URL, the scenario fires immediately.
Execution History and Debugging
Make keeps a detailed execution history for every scenario run. You can click into any past execution and see:
- Exactly what data each module received
- What it outputted
- Where errors occurred
- How long each module took
This is invaluable for debugging. When a workflow breaks at 2 AM, you don't have to guess what happened — you can replay the exact data flow. Zapier has improved here, but Make's execution inspector is still more detailed and easier to navigate.
The "run once" testing mode lets you trigger a scenario manually with real data and step through each module's output, which makes development significantly faster than deploying and waiting for a real trigger.
Make.com Pricing in 2026
Make uses a credit-based system. Every operation (module execution) consumes credits. Here's the current pricing, verified against Make's pricing page in July 2026:
| Plan | Monthly Price | Annual Price (per mo) | Credits/Month | Active Scenarios | Min Interval | Key Features | |---|---|---|---|---|---|---| | Free | $0 | $0 | 1,000 | 2 | 15 min | Core modules, community support | | Core | $10.59 | $9.00 | 10,000 | Unlimited | 1 min | All integrations, basic support | | Pro | $18.82 | $16.00 | 10,000 | Unlimited | 1 min | Custom variables, priority support, full-text log search | | Teams | $34.12 | $29.00 | 10,000 | Unlimited | 1 min | Team roles, shared connections, SSO | | Enterprise | Custom | Custom | Custom | Unlimited | 1 min | Custom functions, 24/7 support, overage protection, dedicated CSM |
Important pricing notes:
- All paid plans start at 10,000 credits/month. Higher tiers (20K, 40K, 80K+) scale proportionally in price.
- Annual billing saves roughly 15%.
- AI module credits are variable — they consume credits based on token usage, not a fixed per-execution amount.
- The free plan's 1,000 credits and 2-scenario limit is enough to test the platform but not enough for real production use.
- No public discount codes exist. Make offers extended free credits for non-profits and educational use on request.
The Credit Math Most Reviews Skip
Here's what catches people: a single scenario execution can consume anywhere from 1 to dozens of credits depending on how many modules run. A 5-module scenario that runs once consumes 5 credits minimum. Run it every minute for a month and you're at 216,000 credits — well beyond the Core plan.
AI modules make this worse because their credit consumption is dynamic. A text classification prompt might use 3 credits, while a long-form generation uses 15, even in the same module. You need to monitor your credit usage carefully during the first month of any AI-heavy workflow.
The counter-argument: even with credit math, Make is typically 3–5x cheaper than Zapier for equivalent automation volume. A workflow that costs $50/month on Zapier often runs for $9–16/month on Make. The savings compound as you scale.
Pros and Cons
What Make Gets Right
- Visual canvas is genuinely powerful. Routers, iterators, error routes, and filters let you build logic that would require code on other platforms. Once you learn the mental model, you build fast.
- Pricing that scales. At 10,000 operations for $9/month (annual), Make is dramatically cheaper than Zapier's equivalent pricing. The gap widens as volume increases.
- 3,000+ integrations plus HTTP. The native app library covers most major tools, and the HTTP module fills every gap. You're never stuck because an integration doesn't exist.
- AI features are real, not bolted on. AI Agents with MCP support, built-in AI Toolkit on all plans, native LLM modules — Make is treating AI as a core capability, not a marketing checkbox.
- Execution history and debugging. The ability to inspect every data point at every step of a past execution makes debugging straightforward.
- Data transformation built in. Functions, formulas, and the new Functions app handle transformations that would take multiple steps on other platforms.
What Make Gets Wrong
- The learning curve is real. "No-code" is technically accurate but misleading. You need to understand data structures, mapping, and logical flow to build anything non-trivial. Plan on a week before you're productive, and several weeks before you're building complex scenarios confidently.
- Credit consumption for AI is unpredictable. Dynamic token-based credits for AI modules make cost planning genuinely difficult. You can't reliably forecast monthly costs for AI-heavy workflows without running them for a month first.
- Error handling is opt-in, not automatic. You have to explicitly design error routes for each module that might fail. There's no global error handler or automatic retry by default. If you forget to add error handling, a failed module just stops the scenario silently.
- Mobile experience is essentially useless. The canvas is desktop-only in practice. Tablets work for monitoring scenario status, but editing on anything smaller than a laptop is painful. If you need to fix a broken automation from your phone, you're out of luck.
- Support is slow on lower-tier plans. Core plan support is email-only and responses can take days. The community forum is active and helpful, but if you need fast answers from Make's team, you'll need Pro or higher.
- Some niche apps have fewer triggers than Zapier. Zapier's 6,000+ app library is larger, and some integrations have more trigger and action options. Make's HTTP module compensates, but it requires more manual setup.
- The UI feels slightly dated. The canvas works well functionally, but the overall interface design hasn't had a major refresh in a while. It's not bad — just not as polished as newer tools.
Who Is Make.com For?
Best fit:
- Operations teams who've outgrown Zapier and need branching logic, loops, or multi-path workflows
- Agencies and freelancers building automations for clients (the visual canvas makes them easy to document and hand off)
- Technical non-developers — people comfortable with data concepts but who don't want to write code
- Small-to-mid businesses watching automation costs — Make delivers significantly more per dollar than Zapier
- AI automation builders who want to integrate LLMs into workflows without managing infrastructure
Not ideal for:
- Complete beginners who need the absolute simplest path to their first automation (Zapier is easier to start with)
- Developers who want full code control and self-hosting (n8n is the better choice)
- Enterprise teams requiring strict compliance, audit logs, and SLA guarantees out of the box (Zapier's enterprise tier is more mature, though Make Enterprise is closing the gap)
- Mobile-first users who need to manage automations from their phone
Make vs Zapier vs n8n: How They Compare
| Feature | Make | Zapier | n8n | |---|---|---|---| | Pricing (entry) | $9/mo (10K ops) | $19.99/mo (750 tasks) | Free (self-hosted) / $24/mo (cloud) | | Free plan | 1,000 ops, 2 scenarios | 100 tasks, 5 zaps | Unlimited (self-hosted) | | Integrations | 3,000+ apps | 6,000+ apps | 400+ native + community nodes | | Workflow style | Visual canvas (branching) | Linear (trigger → actions) | Visual canvas (branching) | | AI features | AI Agents (GA), MCP, AI Toolkit | Zapier Agents (separate billing) | AI agents + human-in-loop | | Error handling | Dedicated error routes (manual) | Basic retry | Full catch routes + retry logic | | Self-hosting | No | No | Yes | | Learning curve | Moderate (~1 week) | Low (~1 hour) | High (requires technical skills) | | Best for | Visual builders who need logic | Non-technical users | Developers and privacy-focused teams | | Cost at scale (10K ops) | ~$9/mo | ~$50+/mo | Free (self-hosted) |
When to choose Make over Zapier: You need branching logic, data transformation, or you're running more than a few hundred operations per month. Make is typically 3–5x cheaper at equivalent volume and significantly more capable for complex workflows.
When to choose Make over n8n: You want the power of a visual canvas without managing your own infrastructure. n8n requires Docker, server maintenance, and technical skills to self-host. n8n Cloud exists but is more expensive than Make and has fewer native integrations.
When to choose Zapier over Make: You're non-technical, need the absolute fastest setup, or require a specific niche integration that Zapier supports but Make doesn't. Zapier's app library is roughly 2x larger.
When to choose n8n over Make: You're a developer who wants code-level control, you need self-hosting for data privacy/compliance, or you're operating at massive scale where n8n's free self-hosted tier makes economic sense.
Bottom Line
Make.com is the automation platform that rewards investment. The first week is harder than Zapier. The canvas mental model takes time. The credit system requires monitoring. But once you're past that initial learning curve, you get a tool that's genuinely more powerful and significantly cheaper than the market leader.
The 2026 additions — AI Agents going GA, MCP support, the Functions app, native LLM modules — have pushed Make from "Zapier alternative" to "automation platform in its own right." If you're building workflows that involve any kind of logic, data transformation, or AI integration, Make is the strongest option in the visual no-code space.
Start with the free plan (1,000 credits, 2 scenarios) to test the canvas experience. If you're ready to build for real, the Core plan at $9/month annual gives you everything you need. Upgrade to Pro only if you need priority support or full-text log search.
Just don't expect to be productive on day one. This is a tool that pays dividends in week two.
This review reflects our independent evaluation of Make.com. We have no affiliate relationship with Make — this is an unsponsored, editorially independent review. Pricing and features verified as of July 2026. Visit make.com for current pricing.