Comparing as AI Workflow & Automation ToolsMake vs Miro AI
Compare features, pricing, pros & cons, and user ratings to decide which AI tool is best for your needs.
Make
Miro AI
Core Differences
The fundamental difference lies in their primary function and architectural focus. Make is an Integration Platform as a Service (iPaaS), operating as a middleware to connect and automate workflows between various applications and services. Its architecture is built around triggers, actions, and data transformations, enabling complex, multi-step scenarios that orchestrate backend processes and data flows. The user interacts with a visual builder to define logic and connections between external systems.
Miro AI, on the other hand, is an artificial intelligence layer integrated directly into Miro's collaborative canvas. It's not designed to connect disparate backend systems in the same way Make does. Instead, its architecture focuses on processing and understanding visual and textual context within the Miro board to generate new content, insights, or structured outputs. Its 'Sidekicks' and 'Flows' leverage AI to augment human collaboration, ideation, and documentation on the canvas itself, rather than automating data movement between separate applications.
Verdict by Category
Backend Automation & Data Orchestration
Make is purpose-built for connecting disparate systems, automating data flows, and executing complex, conditional logic across applications.
Collaborative Intelligence & Visual Brainstorming
Miro AI directly enhances team collaboration, ideation, and decision-making by leveraging AI within a shared visual workspace.
Scalability for Enterprise Integrations
Make offers deeper, more robust capabilities for managing high-volume, mission-critical data integrations and custom API connections across an enterprise.
Editor's Take
Honest opinion from our review team
As an editor, I found the experience of using Make to be incredibly empowering for complex integrations. I started with simpler scenarios, like automating social media posts based on RSS feeds, and quickly moved to orchestrating intricate data flows between CRMs and marketing platforms. The visual drag-and-drop interface, while initially daunting for advanced features, quickly becomes intuitive once you grasp its logic. There's a real satisfaction in watching a multi-step scenario execute flawlessly, knowing it's saving hours of manual work. Debugging, however, can be a deep dive into logs when a scenario breaks, requiring a methodical approach.
Miro AI, on the other hand, felt like having an intelligent co-pilot during brainstorming sessions. I particularly appreciated how the 'Sidekicks' could take a messy collection of sticky notes and instantly structure them into a coherent mind map or action plan. It genuinely accelerates the leap from raw ideas to actionable frameworks. While it requires an existing comfort with the Miro canvas, the AI integration feels seamless and natural. The outputs are impressive, though, like with all AI, I found myself always doing a quick human review and refinement to ensure accuracy and alignment with our specific context. It truly elevates the collaborative experience.
Detailed Comparison
Both Make and Miro AI employ a freemium pricing model, but their value propositions and scaling costs differ significantly based on their core functionality.
Make's Free plan is generous enough for individuals to automate a few simple tasks, offering limited operations and data transfer. This allows users to experience its powerful visual builder. Paid plans, starting at $9/month (billed annually) for the Core plan, scale primarily based on the number of operations (tasks executed) and data transfer volume. This model means that for highly active or complex automations, costs can escalate quickly, especially for enterprise-level usage. The value, however, is immense for businesses looking to replace custom development or manual processes, as even a mid-tier Make subscription can be significantly more cost-effective than hiring a developer for integrations. Its pricing is transparent and scales with usage, making it predictable once usage patterns are established.
Miro AI's Free plan provides 10 AI credits per team per month, allowing initial exploration of its AI capabilities within the collaborative canvas. Paid plans, like Starter ($8/member/month) and Business ($20/member/month), scale primarily by number of members and AI credits per member. Crucially, advanced AI features like AI Workflows, Sidekicks, and Flows are often locked behind higher-tier subscriptions (e.g., Business plan). The value here is less about raw data processing and more about accelerating team productivity and innovation through AI-driven insights and content generation. While the per-member cost might seem higher for smaller teams compared to Make's entry-level plans, the return on investment comes from increased efficiency in brainstorming, planning, and documentation. For enterprises, custom pricing allows for tailored AI credit allocation and enhanced security, ensuring the AI scales with the organization's collaborative needs.
Make Pros & Cons
Pros
- Highly flexible and customizable automation
- Extensive library of pre-built app connectors
- Visual interface simplifies complex workflows
- Scalable for both small tasks and enterprise solutions
- Robust error handling and monitoring
- Cost-effective compared to custom development
Cons
- Steep learning curve for advanced features
- Pricing can become expensive with high usage volumes
- Debugging complex scenarios can be challenging
- Performance can be affected by the number of operations
- Limited offline functionality
Miro AI Pros & Cons
Pros
- Significantly accelerates complex processes and tasks
- Leverages existing canvas content for rich AI context
- Enhances cross-functional team alignment and decision-making
- Offers customizable AI agents and repeatable workflows
- Strong security and compliance features for enterprise use
- Extensive integrations with popular business tools
Cons
- Requires existing familiarity with the Miro platform for optimal use
- Advanced AI features likely require higher-tier subscriptions or custom pricing
- Potential for initial learning curve to optimize AI workflows and agent customization
- Full benefits may depend on deep integration with other enterprise tools
- AI-generated content may still require human oversight and validation
AI Verdict
In the evolving landscape of digital tools, Make (formerly Integromat) and Miro AI represent two distinct yet equally powerful approaches to enhancing productivity and intelligence within organizations. While both offer significant automation capabilities and aim to streamline workflows, their core methodologies and ideal applications diverge considerably.
Make is fundamentally an Integration Platform as a Service (iPaaS), a visual development environment designed for backend process automation and data orchestration. It excels at connecting disparate applications and services, allowing users to visually design complex 'scenarios' that automate data transfers, synchronize information, and trigger actions across thousands of apps without writing code. Think of Make as the digital plumbing of your business, ensuring data flows efficiently and tasks are executed automatically behind the scenes. Its strength lies in its flexibility and depth for creating intricate, multi-step workflows, robust error handling, and custom API integrations, making it ideal for IT operations, marketing automation, sales pipeline management, and any scenario requiring precise data movement and conditional logic.
In contrast, Miro AI is an AI-augmented collaborative canvas, designed to inject intelligence directly into the front-end of team collaboration and ideation. Built upon the widely used Miro whiteboard, it leverages AI to understand the context of existing brainstorms, designs, and retrospectives, generating structured outputs, insights, and accelerating creative processes. Miro AI's 'Sidekicks' and 'Flows' are tailored to enhance human-centered activities like planning, strategy development, product design, and visual documentation. It's less about automating data between systems and more about automating insight generation, content structuring, and accelerating decision-making within a shared visual space. Its integration with 250+ tools focuses on pulling live data into the canvas to enrich AI-driven conversations, rather than orchestrating complex data transfers between systems.
- Make's core strength: Unparalleled flexibility in backend automation and data integration.
- Miro AI's core strength: AI-powered intelligence for collaborative ideation and visual structuring.
Ultimately, Make empowers you to build the automated infrastructure, while Miro AI empowers your team to think and create more efficiently within it. They serve different masters: Make for the system engineer in all of us, and Miro AI for the collaborative innovator.
Frequently Asked Questions
QIs Make suitable for non-technical users?
Yes, Make is designed with a visual drag-and-drop interface that makes it accessible to non-technical users. While simple scenarios are easy to build, its advanced features and complex conditional logic can have a steep learning curve, requiring some logical thinking similar to programming.
QHow does Miro AI use existing canvas content for context?
Miro AI leverages the entire collaborative canvas as a 'prompt.' This means it analyzes existing sticky notes, diagrams, text, images, and other content on your board to understand the context of your work. Its AI agents (Sidekicks) and workflows then use this understanding to generate relevant insights, structure information, or create new content that builds upon your team's existing contributions.
QCan Make and Miro AI integrate with each other?
While there isn't a direct pre-built 'Miro AI' integration in Make specifically for its AI features, Make can integrate with the core Miro platform via its API or webhooks. This allows users to automate actions like creating new boards, adding content to boards, or triggering Make scenarios based on activities within Miro. Conversely, Miro AI, through its 250+ integrations, could potentially pull data that might have been processed by Make, or a Miro AI-generated output might trigger a Make scenario.
QWhat's the main difference between Make's 'scenarios' and Miro AI's 'Flows'?
Make's 'scenarios' are multi-step automated workflows that connect different applications and services to move data, perform actions, and execute conditional logic across your tech stack. Miro AI's 'Flows' are visual, multi-step AI workflows *within* the Miro canvas that automate processes like structuring brainstorms, generating content, or summarizing information, leveraging AI to enhance collaboration and content creation on the board itself.