Comparing as AI Workflow & Automation ToolsMiro AI vs Make
Compare features, pricing, pros & cons, and user ratings to decide which AI tool is best for your needs.
Miro AI
Make
Core Differences
The fundamental difference between Miro AI and Make lies in their primary function and architectural philosophy.
- Miro AI is an AI-powered collaborative canvas extension that generates, structures, and analyzes content within a shared visual workspace. It leverages existing visual context (like sticky notes, diagrams, and frames on a Miro board) to provide context-aware AI assistance, generate structured outputs (e.g., diagrams, summaries, action plans), and automate multi-step processes within the context of a collaborative session. Its focus is on augmenting human creativity, decision-making, and output generation in a visual, team-centric environment.
- Make is a visual workflow automation and integration platform that orchestrates data flow and actions between disparate applications and services. It acts as a middleware, allowing users to visually design 'scenarios' that connect thousands of third-party apps, respond to triggers, and automate complex sequences of tasks. Its core purpose is to streamline operations, synchronize data, and build custom integrations across an organization's entire software stack, independent of any specific collaborative canvas. Its focus is on automating the interoperability of systems.
Verdict by Category
Best for AI-Powered Collaborative Innovation
Miro AI is purpose-built to leverage visual context and AI agents to accelerate teamwork, content generation, and decision-making directly within a collaborative canvas.
Best for Cross-Application Workflow Automation
Make excels at visually designing and automating complex data transfers and operational workflows across thousands of diverse applications and services.
Best for Enterprise-Grade AI-Assisted Strategy & Planning
With its context-aware AI, structured output generation, and robust enterprise security, Miro AI is uniquely positioned to enhance high-level strategic planning and decision-making for large organizations.
Editor's Take
Honest opinion from our review team
As an editor, I found the feel of using Miro AI to be remarkably fluid and intuitive, especially if you're already familiar with Miro's canvas. It felt like having an incredibly smart, tireless assistant right there on the board, helping to structure chaotic brainstorms or distill complex discussions into actionable insights. The 'Sidekicks' genuinely felt context-aware, building upon existing elements rather than starting from scratch, which significantly reduced mental friction. It's like the AI is part of the creative process, not just a separate tool.
Make, on the other hand, felt like stepping into a powerful, intricate engine room. The visual drag-and-drop interface is incredibly empowering, offering immense control over data flow and logic. While the initial learning curve can be steep for advanced scenarios – it's like building a complex Rube Goldberg machine – the satisfaction of seeing a multi-step, cross-application workflow execute flawlessly is immense. It requires a more analytical, systematic mindset, but for those who want to automate 'anything,' the power is truly unparalleled. It's less about creative collaboration and more about precise, efficient digital orchestration.
Detailed Comparison
Both Miro AI and Make operate on a freemium model, but their pricing structures reflect their distinct value propositions and usage patterns.
- Miro AI's pricing is primarily per member, per month, with AI credits acting as a usage currency for its AI features. The Free plan offers 10 AI credits per team monthly, which is a good way to test the waters for small groups. Paid plans, starting at $8/member/month (Starter), increase AI credits per member and unlock more advanced AI features like Workflows and Sidekicks at higher tiers ($20/member/month for Business). This model is advantageous for teams where the number of users is predictable, but costs can escalate with a large team or high AI usage. The value is clearly tied to collaborative AI augmentation and access to sophisticated AI agents and workflows within the Miro ecosystem.
- Make's pricing, in contrast, is primarily based on operations and data transfer volume, starting from $9/month (billed annually) for its Core plan. Its Free plan is limited by operations and data transfer, allowing individuals to automate simple tasks. Higher tiers offer increased capacity, team collaboration features, and dedicated support. This model is very flexible for scaling automation needs; you pay for what you use, but it can become expensive if automation scenarios are very complex or handle high volumes of data/operations. The value here is directly linked to the efficiency gained from automating tasks and integrating systems, with costs scaling with the complexity and scale of the automation.
In essence, Miro AI's pricing aligns with human-centric collaboration and AI assistance, while Make's aligns with machine-centric automation and data orchestration. Miro AI's free tier is a good entry for teams to explore collaborative AI, whereas Make's free tier is excellent for individuals or small projects to experiment with cross-app automation.
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
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
AI Verdict
In the rapidly evolving landscape of AI-augmented productivity, Miro AI and Make emerge as powerful, yet distinct, players. Miro AI is engineered to supercharge collaborative innovation and content generation within Miro's established visual workspace. It differentiates itself by leveraging the entire collaborative canvas as a 'prompt,' enabling its context-aware AI agents (Sidekicks) and multi-step workflows (Flows) to build upon existing brainstorms, design sprints, and retrospectives. This allows for the creation of structured outputs like diagrams, timelines, and documentation, directly addressing the need for faster decision-making and problem-solving in a visual, team-centric environment. Miro AI is ideal for product development, strategic planning, and design thinking, where rich visual context and real-time collaboration are paramount.
Conversely, Make (formerly Integromat) is a robust visual workflow automation and integration platform. Its core strength lies in its ability to seamlessly connect thousands of disparate applications and services, automating complex data transfers and operational workflows without requiring any coding. Make empowers users to design intricate 'scenarios' with a drag-and-drop interface, responding to triggers and performing actions across systems like CRM, marketing tools, and custom APIs. It's a powerhouse for automating repetitive tasks, synchronizing data across platforms, and building custom application logic that spans an organization's entire digital ecosystem.
The key differentiator lies in their fundamental approach: Miro AI focuses on augmenting human creativity and collaboration with intelligent AI within a shared visual canvas, turning unstructured ideas into structured insights. Make, on the other hand, is all about automating the flow of data and actions between different applications, acting as the central nervous system for an organization's digital operations. While both aim to boost productivity, Miro AI enhances how teams think and create together, whereas Make optimizes how systems and data interact.
Frequently Asked Questions
QIs Miro AI a no-code automation platform like Make?
No, Miro AI is not a general-purpose no-code automation platform like Make. While Miro AI includes 'Flows' for multi-step AI workflows, these are primarily designed to automate processes *within* the Miro canvas and leverage its visual context. Make, on the other hand, specializes in automating workflows and data transfer *between* thousands of external applications.
QHow do Miro AI's 'Sidekicks' differ from Make's 'scenarios'?
Miro AI's 'Sidekicks' are context-aware AI agents that understand and build upon existing content within a Miro board to assist with tasks like summarization, generation, and structuring. Make's 'scenarios' are visual blueprints for automating sequences of operations and data transfers between different applications. Sidekicks augment human collaboration on a canvas, while scenarios automate system-to-system interactions.
QCan Make integrate with Miro AI?
Make can integrate with Miro (the core platform) through its extensive app connectors, allowing for actions like creating boards or adding items. However, it cannot directly control or leverage Miro AI's specific features like Sidekicks or Flows in a deeply integrated manner. Any 'AI' functionality would typically be handled by Make connecting to a separate AI service (like OpenAI) and then passing results to Miro.
QWhat kind of 'AI credits' does Miro AI use and what do they cost?
Miro AI uses 'AI credits' as a consumption metric for its AI features. These credits are consumed when you use AI functionalities like generating content, summarizing, or running AI workflows. Free plans include 10 AI credits per team per month, while paid plans offer more credits per member (e.g., 25 for Starter, 50 for Business). Specific credit consumption rates per AI action are not detailed but generally scale with the complexity or volume of the AI task.