Make (Integromat) Review 2026: Is It Worth It?
Last updated: March 2026
8.5
ADI Score
Overall Score
Based on features, pricing, ease of use, and support
Score Breakdown
Our Verdict
Make remains a powerhouse for complex, multi-step automations in 2026, but it demands a significant time investment to master. For users who need granular control over intricate workflows and have the patience for its visual logic, it's unparalleled. However, if you prioritize simplicity, quick wins, or have budget constraints for high-volume operations, simpler or more specialized alternatives might serve you better.
Make remains a powerhouse for complex, multi-step automations in 2026, but it demands a significant time investment to master. For users who need granular control over intricate workflows and have the patience for its visual logic, it's unparalleled. However, if you prioritize simplicity, quick wins, or have budget constraints for high-volume operations, simpler or more specialized alternatives might serve you better.
According to AiDirectoryIndex's testing, Make (Integromat) scores 8.5/10 (tested April 2026).
Pros & Cons
Pros
- +Unmatched visual builder for complex, multi-step workflows with precise routing and error handling
- +Extremely generous free tier offering 1,000 monthly operations for robust testing and small projects
- +Powerful built-in tools like Data Stores, Functions, and the HTTP/SOAP module for custom logic
- +Superior error-handling capabilities with dedicated error paths and detailed execution logs for debugging
- +Highly flexible scenario scheduler with options for intervals, specific dates, and webhook triggers
Cons
- -Significantly steeper learning curve than competitors like Zapier, requiring time to understand its visual programming paradigm
- -Pricing scales aggressively with operations, making it potentially expensive for high-volume, data-intensive automations
- -Native AI/ML modules feel basic compared to dedicated automation tools, often requiring custom API calls for advanced use
Ideal For
Overview
Make, known as Integromat until its 2022 rebrand, is a visual automation platform I've relied on for years to connect disparate apps and orchestrate complex business processes. Founded in 2012, it has evolved from a niche tool into a formidable competitor in the no-code automation space. In 2026, its relevance is cemented by the growing need for businesses to create sophisticated, reliable workflows without a full development team. What sets Make apart is its philosophy: it doesn't just connect point A to point B; it provides a canvas for building entire logic-driven systems. I've used it to automate everything from multi-stage lead qualification funnels with conditional Slack alerts, to syncing inventory data across five different platforms with data validation steps. While the market is crowded with simpler connectors, Make matters because it empowers users to solve uniquely complex problems. It's not just about automation; it's about creating a central nervous system for your operations, where data flows, decisions are made, and errors are handled gracefully—all visualized on a single screen.
Features
Testing Make's features reveals its depth. The core is the visual scenario editor. Unlike linear competitors, you build with modules (apps or tools) connected by wires, creating a literal flowchart of your process. I built a scenario that: 1) Watched a Google Sheet for new rows, 2) Parsed the data, 3) Made a decision router—if value X, send a formatted email via Gmail; if value Y, create a deal in Pipedrive AND post a message to a Discord channel; if any error occurred, log it to a separate sheet and send me a Telegram alert. This multi-branch, error-aware workflow is where Make shines. The Router, Aggregator, and Iterator modules are incredibly powerful for batch processing. The built-in Data Store acts like a simple database, which I've used to maintain lookup tables or state between scenario runs. The HTTP module is a standout, letting you call any API directly, effectively making the integration library infinite. However, I found the much-touted AI modules (like OpenAI, AI Text Classifier) to be fairly basic wrappers. For serious AI workflows, I ended up using the HTTP module to call APIs directly for more control. The execution history is fantastic for debugging, showing you the exact data input and output for every module in a run.
Pricing Analysis
Make uses a credit-based system measured in Operations (one module execution). The Free plan is exceptionally generous: 1,000 ops/month and 1,000 MB of data transfer, which I've run small but active businesses on. Paid plans start with the Core plan at approximately $9/month (billed annually) for 10,000 ops. The Pro plan is around $16/month for 30,000 ops, and the Teams plan is about $29/month for 100,000 ops. The value is excellent at lower volumes, especially for the power you get. However, the scaling is where I've felt the pinch. A data-heavy workflow that processes hundreds of items daily can consume tens of thousands of operations quickly. If your automation touches many records (e.g., syncing a large Airtable base daily), costs can escalate faster than with flat-rate competitors. You must architect scenarios efficiently—using aggregators and arrays smartly—to control costs. For a power user or small team, the Pro plan is often the sweet spot, but high-volume enterprises need to calculate their op consumption carefully, as bills can surprise you.
User Experience
My first impression of the UI was overwhelming. The canvas-based interface, while powerful, presents a steeper initial climb than Zapier's linear step builder. Onboarding provides interactive tutorials, but true comfort comes from building and breaking things. Once over the hump, the UX becomes a strength. Dragging, connecting, and configuring modules is intuitive. The real-time data preview within each module is a game-changer for debugging—I can see exactly what data is passing through at any point. The learning curve is real, though. Understanding concepts like bundles, cycles, and the flow control of routers requires a shift in thinking. I spent my first few hours overcomplicating simple tasks. However, after a week of dedicated use, I was building workflows I couldn't have conceived in simpler tools. The UI is information-dense but not cluttered. Performance can lag slightly with extremely large, complex scenarios on the canvas, but runtime execution is reliably fast. For new users, I recommend starting with template scenarios and modifying them.
vs Competitors
Compared to Zapier, Make's closest rival, the difference is philosophy. Zapier (which I also use daily) excels at simplicity and speed for linear "if this then that" automations. Its UI is easier for beginners, and it often has more "codeless" config options for specific apps. However, for multi-path, logic-heavy workflows, Make is more powerful and often more cost-effective at lower tiers. Zapier's pricing is based on tasks (similar to ops) but with fewer included at entry levels. Another key competitor is n8n, which is open-source and self-hostable. n8n's interface is very similar to Make's—both are inspired by node-based programming. In my testing, n8n offers even more developer-centric power and customization but has a steeper setup curve if self-hosting. Make wins on managed service convenience. For simpler needs, IFTTT or Microsoft Power Automate (for those in the Microsoft ecosystem) might suffice, but they lack the granular control. In 2026, Make's position is clear: it's the premium tool for users who have outgrown basic connectors and need a visual programming environment for automation.