Ivern vs Make (Integromat): AI Agent Orchestration vs Visual Automation

Ivern and Make (formerly Integromat) both help teams automate work, but they automate fundamentally different types of tasks.

Ivern orchestrates AI agent squads -- teams of specialized AI agents that collaborate on intelligent tasks like research, writing, coding, and analysis. Make connects applications through visual workflow scenarios, moving data between SaaS tools based on triggers and conditions.

This comparison helps you pick the right platform -- or learn how to use both together.

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Quick Comparison

Feature	Ivern	Make
Type	AI agent orchestration platform	Visual workflow automation platform
Primary Use	Coordinate AI agents on intelligent tasks	Connect apps and automate data flows
Target User	Teams using AI for complex work	Operations teams automating processes
AI Capability	Core feature -- multi-agent squads	Limited -- OpenAI module and HTTP modules
Workflow Model	Task-based: agents figure out execution	Scenario-based: visual trigger → action flows
Coding Required	None	None (functions for advanced logic)
Integrations	Claude, OpenAI, Cursor, OpenCode, REST APIs	1,800+ app integrations
BYOK	✅ Zero markup	Via direct API modules
Real-time Streaming	✅ Live agent collaboration	❌ Execution log monitoring
Pricing	Free (15 tasks), Pro $29/month	Free tier (1,000 ops), paid from €9/month

What is Ivern?

Ivern is an AI Agent Orchestration Hub that connects your existing AI tools -- Claude Code, Cursor, OpenAI, OpenCode -- into coordinated squads that execute real work through a web interface.

How Ivern Works

1. Connect your AI tools (Claude, OpenAI, Cursor)
2. Choose agent roles -- Researcher, Writer, Coder, Reviewer, and more
3. Build squads -- combine agents with complementary skills
4. Assign tasks -- describe what you need done
5. Watch live -- stream agent collaboration in real time

What Makes Ivern Different

• Multi-agent coordination: Multiple AI agents with distinct roles collaborate on tasks
• Cross-provider: Mix Claude, OpenAI, Cursor, and OpenCode in one squad
• Intelligent execution: Agents reason about tasks and adapt their approach
• Real-time visibility: Watch agents think, decide, and hand off work live
• No-code: Web dashboard with pre-built role templates

Ivern Excels At

• Content creation pipelines (research → write → edit → publish)
• Code review and testing workflows
• Multi-source research and analysis
• Any task requiring AI reasoning and collaboration

What is Make?

Make (formerly Integromat) is a visual automation platform that connects 1,800+ applications through drag-and-drop scenarios. You define triggers and actions to move data between apps automatically.

How Make Works

1. Create a scenario -- visual canvas with connected modules
2. Add a trigger -- webhook, schedule, app event, or manual
3. Add modules -- app actions (send email, create record, update spreadsheet)
4. Add logic -- filters, routers, iterators for branching and looping
5. Activate -- scenario runs automatically based on trigger

What Makes Make Different

• 1,800+ integrations: Connect nearly any SaaS tool
• Visual scenario builder: Drag-and-drop canvas for designing workflows
• Data transformation: Built-in functions for manipulating data between steps
• Error handling: Define fallback paths and retry logic
• Execution history: Detailed logs of every scenario run

Make Excels At

• App-to-app data synchronization
• Email marketing automation
• CRM and sales pipeline automation
• Social media cross-posting
• Any workflow moving data between SaaS tools

Head-to-Head Feature Comparison

1. AI and Intelligence

Ivern:

• AI is the core product
• Multiple AI agents collaborate with distinct roles
• Agents reason about tasks, make decisions, adapt
• Cross-provider: Mix Claude, OpenAI, Cursor
• Real-time streaming of agent thought processes

Make:

• AI is one integration among many
• OpenAI module for text generation and analysis
• HTTP modules for connecting to custom AI APIs
• No multi-agent coordination
• No real-time AI collaboration features

Winner: Ivern for AI intelligence. Make for app connectivity.

2. Integration Ecosystem

Ivern:

• AI tool connections: Claude Code, Cursor, OpenAI, OpenCode
• REST API for custom integrations
• Webhook support
• Focused on AI agent ecosystem

Make:

• 1,800+ pre-built app integrations
• HTTP module for any API
• Database connectors, file storage, email services
• E-commerce, CRM, marketing, and productivity tools
• Community-built templates

Winner: Make -- one of the broadest integration ecosystems available.

3. Workflow Design

Ivern:

• Task-based: You describe what you need, agents decide how to do it
• Flexible and adaptive -- agents adjust approach based on the task
• Human-in-the-loop: Review results and iterate
• Focus on intelligent task execution

Make:

• Scenario-based: You design the exact flow of data between apps
• Deterministic -- same input, same output every time
• Visual canvas with branching, looping, error handling
• Focus on structured data flow automation

Winner: Depends on use case. Ivern for intelligent tasks. Make for structured flows.

4. Ease of Use

Ivern:

• Template-based agent setup
• Task description interface -- natural language input
• Real-time streaming shows agent progress
• Learning curve: Low -- 5 minutes

Make:

• Visual drag-and-drop scenario builder
• Need to understand data structures and mapping
• Functions and formulas for advanced transformations
• Learning curve: Medium -- 1-2 hours for basics

Winner: Ivern for quick start. Make offers more power with more complexity.

5. Pricing Comparison

Ivern:

• Free: 15 tasks, 3 squads, unlimited agent connections
• Pro: $29/month -- unlimited tasks and squads
• BYOK: Zero markup on AI API usage

Make:

• Free: 1,000 operations/month, 2 active scenarios
• Core: €9/month -- 10,000 operations
• Pro: €16/month -- 10,000 operations + priority execution
• Teams: €29/month -- per user, shared scenarios
• Enterprise: Custom pricing

Winner: Make for high-volume simple automation. Ivern for AI-focused tasks.

Real-World Scenarios

Scenario 1: Lead Processing Pipeline

Goal: Process incoming leads with AI enrichment.

Ivern approach:

1. Create Research Squad with Researcher and Analyst agents
2. Submit lead for analysis
3. Agents research company, analyze fit, generate report
4. Manual review and routing

Make approach:

1. Trigger: New lead in Typeform
2. Module: Enrich with Clearbit
3. OpenAI module: Generate personalized email
4. Module: Add to HubSpot CRM
5. Module: Send Slack notification
6. Module: Add to Google Sheets

Winner: Make for end-to-end automation. Ivern for AI-powered analysis quality.

Scenario 2: Blog Content Production

Goal: Research, write, and publish blog posts with AI.

Ivern approach:

1. Create Content Squad: Researcher + Writer + Editor
2. Submit topic
3. Agents research competitors, write draft, edit for quality
4. Review and publish
5. High-quality multi-agent output

Make approach:

1. Trigger: Schedule (weekly)
2. OpenAI module: Generate topic ideas
3. OpenAI module: Write blog draft
4. Module: Create WordPress draft
5. Module: Post to social media
6. Automated but single-model output

Winner: Ivern for content quality. Make for distribution automation.

Scenario 3: E-commerce Order Processing

Goal: Automate order fulfillment across multiple systems.

Ivern approach:

• Not designed for structured data processing
• Could analyze order patterns or generate responses
• Manual handling required

Make approach:

1. Trigger: New Shopify order
2. Module: Create shipment in ShipStation
3. Module: Update inventory in Airtable
4. Module: Send confirmation email via Gmail
5. Module: Add customer to Mailchimp
6. Module: Log in Google Sheets
7. Fully automated end-to-end

Winner: Make -- built for multi-app data workflows.

The Power of Using Both

The most effective teams use Ivern and Make together:

Make (automation) → Ivern (AI intelligence) → Make (distribution)

Example content workflow:

1. Make triggers: Schedule runs weekly, pulls trending topics from RSS
2. Make calls Ivern API: Submits topic to Content Squad
3. Ivern agents research, write, and edit the blog post
4. Ivern returns completed content via API
5. Make distributes: Publishes to WordPress, posts to social media, adds to newsletter

You get AI quality from Ivern and automation breadth from Make.

FAQ

Is Make free?

Make has a free tier with 1,000 operations/month and 2 active scenarios. Paid plans start at €9/month.

Can Make handle AI tasks?

Make has an OpenAI module and HTTP modules for connecting to AI APIs. However, it lacks multi-agent coordination, role-based agents, and real-time collaboration features that Ivern provides.

Which is easier to learn?

Ivern is simpler -- template-based setup with natural language tasks. Make requires understanding data flow concepts but offers a visual editor that's intuitive once you learn the basics.

Do they compete with each other?

Not directly. Ivern automates intelligent AI tasks. Make automates app-to-app data flows. They complement each other when combined.

Get Started

Try Ivern Free

Ready to coordinate AI agent squads?

1. Sign up at ivern.ai/signup
2. Connect your API keys
3. Create a squad with agent roles
4. Assign your first task

15 free tasks. No credit card.

Try Make

Want to automate workflows across your apps?

• Make Website
• Make Templates
• Make Academy

Conclusion

Ivern and Make solve different automation problems. Ivern orchestrates AI agents for intelligent tasks -- research, writing, coding, analysis -- through a no-code dashboard. Make connects 1,800+ apps through visual workflow scenarios for structured data automation.

Use Ivern when you need AI agents to collaborate on complex, intelligent tasks. Use Make when you need to move data between apps automatically. Use both for maximum automation power.

Start orchestrating your AI squads at ivern.ai/signup.