10 Best Make (Integromat) Alternatives for AI Automation (2026)

Make (formerly Integromat) excels at visual automation -- connecting 1,500+ apps through drag-and-drop scenarios. But as teams push into AI agent workflows, Make's limitations become clear: AI is an API module, not a first-class capability. There's no multi-agent orchestration, no agent collaboration, and no way to assign open-ended tasks to intelligent agents. If your automation needs are shifting toward AI, these alternatives deserve a look.

Related guides: Ivern vs Make Comparison · Ivern vs Zapier · AI Workflow Automation Tools 2026 · All Comparisons

Quick Comparison Table

Platform	Focus	AI-First	No Code	Free Tier
Ivern	AI agent orchestration	Yes	Yes	Yes (15 tasks)
Zapier	App automation	No	Yes	Yes
n8n	Automation platform	Partial	Yes	Yes (self-hosted)
Dify	LLM app builder	Yes	Optional	Yes
Flowise	Visual AI builder	Yes	Yes	Yes (open-source)
CrewAI	Agent framework	Yes	No	Yes (open-source)
AutoGen	Agent framework	Yes	No	Yes (open-source)
Workato	Enterprise automation	No	Yes	No (enterprise)
Tray.io	Enterprise automation	No	Yes	No (enterprise)
Relevance AI	AI agent platform	Yes	Yes	Yes

1. Ivern -- Best AI-First Make Alternative

Make connects apps. Ivern connects AI agents. If your workflows increasingly involve AI doing intelligent work -- research, writing, coding, analysis -- rather than just moving data between apps, Ivern is the better fit.

Create AI agent squads through a web interface. Assign tasks like "research competitor pricing and write a comparison report" or "review this pull request and suggest improvements." Agents collaborate, share context, and deliver results -- without you designing every step of the process.

Why teams switch from Make to Ivern for AI

• AI agents, not API calls: Make's OpenAI module sends a prompt and gets a response. Ivern's agents reason, iterate, and collaborate across multiple steps.
• BYOK pricing: Bring your own API keys. Pay wholesale model prices with zero markup. Make charges per operation, and AI-heavy scenarios get expensive fast.
• Task-based execution: Describe the outcome you want. Agents determine the process. Make requires you to design every step of every scenario.
• Multi-agent collaboration: Researchers pass findings to writers, who pass drafts to reviewers. Make's AI modules operate in isolation.
• Cross-provider flexibility: Use Claude for analysis, GPT-4 for writing, Gemini for research -- in the same squad. Make locks each module to one provider.
• No scenario design overhead: Skip the visual flowchart. Assign tasks and let agents work.

When to pick Ivern over Make

Your team is spending more time on AI-powered work (content creation, research, code review) than on app-to-app automation. You want to assign goals, not design workflows.

Build your first AI agent squad free →

2. Zapier

Zapier is Make's most direct competitor -- simpler but with more integrations. Its AI features are growing but still limited.

Strengths over Make

• 6,000+ integrations vs Make's 1,500+
• Simpler setup for basic automations
• More reliable with enterprise SLA
• AI-powered features like AI Actions

Limitations

• Linear trigger-action model -- less complex than Make's scenarios
• AI capabilities are basic API calls
• No multi-agent orchestration
• Per-task pricing expensive for complex workflows

Best for: Teams that want the most app integrations with simple trigger-action automation.

3. n8n

n8n is the open-source alternative to Make with similar visual automation capabilities and growing AI features.

Strengths over Make

• Open-source with self-hosted option
• Growing AI agent nodes
• More affordable for high-volume workflows
• Active community development

Limitations

• Fewer integrations than Make (400+ vs 1,500+)
• Less polished interface
• AI features are newer and less mature
• Self-hosting requires DevOps resources

Best for: Teams wanting open-source automation with control over their infrastructure.

4. Dify

Dify is an AI-first application builder with visual workflow design. It targets teams building LLM applications rather than app automation.

Strengths over Make for AI

• Purpose-built for AI workflows, not app automation
• Built-in RAG pipeline for document-aware AI
• Visual AI workflow designer
• Self-hosted option available

Limitations

• Fewer app integrations than Make
• Limited multi-agent capabilities
• Focused on AI applications, not general automation
• Smaller community and template library

Best for: Teams building AI applications with RAG needs who don't need extensive app integrations.

5. Flowise

Flowise provides a drag-and-drop interface specifically for building LLM workflows. It's the simplest way to create AI chains visually.

Strengths over Make for AI

• Purpose-built for LLM workflows
• Visual drag-and-drop for AI chains
• Open-source and free
• Fast prototyping for AI applications

Limitations

• Only handles AI -- no app automation
• Not designed for production scale
• Limited multi-agent capabilities
• Smaller ecosystem than Make

Best for: Quick AI workflow prototyping where Make's full automation suite isn't needed.

6. CrewAI

CrewAI is a Python framework for role-based multi-agent systems. It's the code-driven answer to AI agent orchestration.

Strengths over Make for AI

• True multi-agent collaboration with role-based design
• Task-driven execution built for AI work
• More sophisticated agent coordination
• Growing template library for agent workflows

Limitations

• Requires Python development
• No visual interface
• No app integrations
• Steeper learning curve than Make

Best for: Developers building custom multi-agent systems who don't need visual automation.

7. AutoGen (Microsoft)

AutoGen enables multi-agent conversations backed by Microsoft Research. Agents chat with each other to solve complex problems.

Strengths over Make for AI

• Robust multi-agent conversation system
• Strong for code generation and research
• Microsoft backing ensures development continuity
• Flexible agent interaction patterns

Limitations

• Requires Python development
• No visual interface or app integrations
• Narrow focus on conversational agents
• Not designed for workflow automation

Best for: Research teams building conversational multi-agent systems.

8. Workato

Workato is an enterprise automation platform with AI capabilities. It's Make for larger organizations with bigger budgets.

Strengths over Make

• Enterprise-grade security and compliance
• More robust error handling and monitoring
• Recipe lifecycle management for teams
• Stronger API management

Limitations

• Enterprise pricing (significantly more expensive than Make)
• Complex setup requiring technical knowledge
• AI capabilities are add-ons, not core features
• Overkill for small and mid-size teams

Best for: Enterprise teams that need governance, compliance, and scale in their automation.

9. Tray.io

Tray.io is another enterprise automation platform with a visual builder. It's more flexible than Make for complex integrations.

Strengths over Make

• More flexible connector architecture
• Better for complex data transformation
• Enterprise-grade reliability
• Strong API building tools

Limitations

• Enterprise pricing
• Steeper learning curve than Make
• AI capabilities are limited
• More technical than Make's interface suggests

Best for: Enterprise teams with complex integration requirements.

10. Relevance AI

Relevance AI is a no-code AI agent platform for business use cases -- sales outreach, customer support, market research.

Strengths over Make for AI

• Purpose-built for AI agents
• No-code agent builder
• Business-focused templates
• Built-in knowledge base for agents

Limitations

• Narrow scope -- specific business use cases
• Not a general automation platform
• Fewer integrations than Make
• Pricing can add up with heavy usage

Best for: Business teams that want pre-built AI agents for specific tasks like sales and support.

Choosing the Right Make Alternative

What You Need	Best Choice
AI agent orchestration (no code)	Ivern
Most app integrations	Zapier
Open-source automation	n8n
Visual AI app building	Dify
Quick AI prototyping	Flowise
Custom multi-agent systems	CrewAI
Enterprise automation	Workato or Tray.io

Why Ivern is the AI-forward choice

Make is excellent at what it does -- connecting apps through visual scenarios. But "connecting apps" and "coordinating AI agents" are fundamentally different problems. Make treats AI as one more API to call. Ivern treats AI agents as the entire product. If your team's future involves more AI work and less app shuffling, Ivern's squad-based approach is built for that future.

Start orchestrating AI agents for free →

Frequently Asked Questions

Is Make good for AI workflows?

Make works for simple AI workflows -- call the OpenAI API within a scenario, process the response, pass it to the next step. But it lacks multi-agent collaboration, can't handle open-ended tasks, and charges per operation. For AI-first workflows, Ivern or purpose-built AI platforms are better choices.

What's cheaper than Make for AI workflows?

Ivern's BYOK model is often cheaper for AI workflows because you pay wholesale API prices without per-operation fees. n8n's self-hosted version is free. Flowise is free and open-source but limited to AI workflows.

Can Make and Ivern work together?

Absolutely. Use Make for app automation (sync CRM data, route emails, manage spreadsheets) and Ivern for AI agent work (research, content creation, analysis). They complement each other well -- Make handles the deterministic workflows, Ivern handles the intelligent work.

Which Make alternative is best for non-technical teams?

Ivern requires zero code for AI agent orchestration. Zapier is simplest for basic automation. Both are significantly more accessible than Make's scenario builder, which has a steeper learning curve despite being visual.