Quick Verdict: Make vs Zapier vs Draft’n Run

Choose Make if: You need complex automation workflows with advanced logic and 1000+ app integrations.

Choose Zapier if: You want the simplest setup with the largest ecosystem (5000+ apps) and are willing to pay premium prices.

Choose Draft’n Run if: Your workflows involve AI, LLMs, RAG, or agent orchestration - it’s purpose-built for AI-native automation.

Three-Way Feature Comparison

Feature	Make	Zapier	Draft'n Run	Winner
AI-Native Design	❌ Add-on	❌ Add-on	✅ Built-in	🏆 Draft'n Run
LLM Support	⚠️ Via HTTP	⚠️ Via HTTP	✅ Native all models	🏆 Draft'n Run
RAG Capabilities	❌ None	❌ None	✅ Advanced	🏆 Draft'n Run
Agent Orchestration	❌ None	❌ None	✅ Multi-agent	🏆 Draft'n Run
Visual Builder	✅ Excellent	✅ Simple	✅ DAG editor	🤝 All good
App Integrations	1000+	5000+	100+ AI-focused	🏆 Zapier
Pricing (Starter)	$9/mo	$20/mo	$0/mo	🏆 Draft'n Run
Free Tier	1,000 ops/mo	100 tasks/mo	1,000 runs/mo	🏆 Make/Draft'n Run
Self-Hosting	❌ No	❌ No	✅ Yes	🏆 Draft'n Run
Observability	Basic logs	Basic logs	Full tracing	🏆 Draft'n Run
Learning Curve	Moderate	Easy	Moderate	🏆 Zapier
Enterprise Features	✅ Yes	✅ Yes	✅ Yes	🤝 All good

Core Differences Explained

Make (formerly Integromat)

Philosophy: Visual automation with advanced logic and data transformation.

Strengths:

• Complex workflow building
• Advanced routers and filters
• Data transformation tools
• Cost-effective pricing
• Visual scenario designer

Weaknesses:

• No native AI capabilities
• Steeper learning curve than Zapier
• Smaller ecosystem than Zapier

Zapier

Philosophy: Simplicity first, connect everything with minimal configuration.

Strengths:

• Largest app ecosystem (5000+)
• Easiest to use
• Great documentation
• Strong brand recognition
• Reliable uptime

Weaknesses:

• Most expensive option
• Limited AI capabilities
• No self-hosting
• Basic logic capabilities

Draft’n Run

Philosophy: AI-first automation with advanced LLM and agent capabilities.

Strengths:

• Native LLM integration (GPT-4, Claude, Gemini, etc.)
• Advanced RAG with vector databases
• Multi-agent orchestration (CrewAI)
• Self-hosting option
• Full observability (OpenTelemetry)
• Open-source foundation

Weaknesses:

• Smaller non-AI integration ecosystem
• More technical (for advanced features)
• Newer platform

Use Case Breakdown

Best for Make:

🔄 Complex Automation

• Multi-step workflows
• Data transformations
• Conditional logic
• E-commerce automation
• CRM synchronization

💰 Cost-Conscious Teams

• More operations per dollar
• Predictable pricing
• Good free tier

🎯 SaaS Integration

• Connecting business tools
• Marketing automation
• Sales workflows

Best for Zapier:

👥 Non-Technical Users

• Simple point-and-click
• Pre-built templates (Zaps)
• Minimal configuration
• Quick setup

🌐 Maximum Integrations

• Niche app connections
• Long-tail integrations
• New app support

📊 Standard Business Workflows

• Lead capture
• Email automation
• Task management
• Basic integrations

Best for Draft’n Run:

🤖 AI-Powered Workflows

• Document Q&A systems
• AI content generation
• Intelligent routing
• Semantic search

🧠 Advanced AI Use Cases

• Multi-agent systems
• RAG applications
• Custom LLM workflows
• Knowledge base interrogation

🔒 Enterprise AI

• Self-hosted deployments
• Data privacy requirements
• Custom model integration
• Full observability

Pricing Comparison

Make Pricing

Free:            $0/mo
- 1,000 operations
- 2 active scenarios
- 15-minute intervals

Core:            $9/mo
- 10,000 operations
- Unlimited scenarios
- 1-minute intervals

Pro:             $16/mo
- 10,000 operations
- Priority support
- Advanced features

Teams:           $29/mo per user
- Team collaboration
- Advanced admin

Zapier Pricing

Free:            $0/mo
- 100 tasks/month
- Single-step Zaps
- Basic features

Starter:         $20/mo
- 750 tasks/month
- Multi-step Zaps
- Premium apps

Professional:    $49/mo
- 2,000 tasks/month
- Unlimited Zaps
- Priority support

Team:            $69/mo per user
- 50,000 tasks/month
- Team features

Draft’n Run Pricing

Free:            $0/mo
- 1,000 workflow runs
- All AI features
- Community support
- Self-hosted option

Professional:    $49/mo
- 10,000 runs/month
- Priority support
- Advanced monitoring

Enterprise:      Custom
- Unlimited runs
- SLA guarantees
- Custom deployment
- Dedicated support

AI Capabilities Comparison

Make AI Features

⚠️ Limited AI Support

• OpenAI via HTTP module
• Manual prompt management
• No RAG capabilities
• No agent support
• Custom code required

Example:

// Make: Manual HTTP calls to OpenAI
// Requires custom JSON formatting
// No native LLM support

Zapier AI Features

⚠️ Basic AI Integration

• OpenAI app available
• ChatGPT actions
• Limited models
• No RAG support
• No agent orchestration

Example:

Trigger → ChatGPT Action → Save Response
Simple but limited

Draft’n Run AI Features

✅ Advanced AI Native

• All major LLMs built-in
• Native RAG with vector databases
• Multi-agent orchestration (CrewAI)
• Custom model integration
• Prompt optimization
• Token management
• AI-specific monitoring

Example:

# Draft'n Run: Native AI workflow
workflow = Workflow("ai-assistant")

workflow.add(RAGRetrieval(
    index="docs",
    retrieval_mode="hybrid"
))

workflow.add(MultiAgentCrew(
    agents=[researcher, analyst, writer]
))

workflow.add(LLMResponse(
    model="gpt-4",
    streaming=True
))

Performance Benchmarks

Metric	Make	Zapier	Draft’n Run
Execution Speed	<1s	<2s	<1s
AI Query Speed	N/A	~2s	<1s
Uptime SLA	99.5%	99.7%	99.9% (Enterprise)
Concurrent Tasks	Unlimited	Plan-limited	Plan-limited
Max Workflow Steps	Unlimited	100	Unlimited

Integration Ecosystems

Make Integrations (1000+)

Categories:

• Marketing (HubSpot, Mailchimp)
• CRM (Salesforce, Pipedrive)
• E-commerce (Shopify, WooCommerce)
• Productivity (Google, Microsoft)
• Custom HTTP/SOAP/FTP

AI/ML: Limited, manual setup

Zapier Integrations (5000+)

Categories:

• Everything Make has +
• Long-tail apps
• Newer SaaS tools
• Premium apps
• AI apps (basic)

AI/ML: Basic OpenAI, limited

Draft’n Run Integrations (100+ AI-focused)

Categories:

• LLMs: OpenAI, Anthropic, Google, Cohere, Ollama
• Vector DBs: Qdrant, Pinecone, Weaviate, Chroma
• Business Tools: Slack, Teams, Notion, Drive
• Databases: PostgreSQL, MongoDB, Redis
• Dev Tools: GitHub, GitLab, Jira

AI/ML: Comprehensive, native

Migration Scenarios

From Zapier to Make

Reason: Cost savings, more complex logic needed Difficulty: Easy to Moderate Timeline: 1-2 weeks

Steps:

1. Export Zap configurations
2. Rebuild scenarios in Make
3. Test thoroughly
4. Switch over

From Make/Zapier to Draft’n Run

Reason: Adding AI capabilities Difficulty: Moderate Timeline: 2-4 weeks

Steps:

1. Identify AI-eligible workflows
2. Rebuild with AI components
3. Keep Make/Zapier for non-AI
4. Gradual migration

Using Multiple Platforms

Best Approach:

• Zapier/Make: General automation
• Draft’n Run: AI workflows
• Integration: Webhooks between platforms

Real-World Examples

Example 1: Customer Support

Make Approach:

Trigger: New email
→ Parse email content
→ Check CRM for customer
→ Route to team member
→ Send confirmation

Zapier Approach:

Trigger: New email
→ Add to Zendesk
→ Notify team in Slack

Draft’n Run Approach:

Trigger: New email
→ RAG search knowledge base
→ AI agent analyzes issue
→ Generate response (or escalate)
→ Send with citations
→ Update CRM

Example 2: Content Generation

Make: Not ideal, requires external AI service

Zapier: Basic ChatGPT integration

Draft’n Run:

Trigger: New topic
→ Research agent searches web
→ Analyst agent extracts insights
→ Writer agent creates content
→ Editor agent reviews
→ Publish to CMS

Decision Matrix

Frequently Asked Questions

Can I use all three platforms together?

Yes! Many teams use Zapier/Make for general automation and Draft’n Run for AI workflows. They can communicate via webhooks and APIs.

Which is most cost-effective?

For general automation: Make offers best value. For AI workflows: Draft’n Run (free tier + open source). Zapier is most expensive but easiest.

Which has the best learning resources?

Zapier has the most tutorials and guides. Make has good documentation. Draft’n Run has technical docs and AI-specific guides.

Can Draft'n Run replace Make or Zapier completely?

For AI workflows: Yes, completely. For general app automation: Make/Zapier have broader ecosystems, but Draft’n Run covers most common integrations.

Which platform scales better?

All three scale well. Draft’n Run offers self-hosting for unlimited scale. Make/Zapier scale vertically within their cloud infrastructure.

Feature Comparison Matrix

Capability	Make	Zapier	Draft’n Run
AI Native	❌	❌	✅✅
General Automation	✅✅	✅✅	✅
Visual Builder	✅✅	✅	✅✅
Integrations	✅✅	✅✅	✅
Price Value	✅✅	⚠️	✅✅
Ease of Use	✅	✅✅	✅
AI/ML Features	❌	⚠️	✅✅
Self-Hosting	❌	❌	✅✅
Enterprise	✅	✅✅	✅✅

Final Recommendation

For Traditional Automation: Make offers the best balance of features and price. Zapier if you prioritize ease of use.

For AI Workflows: Draft’n Run is the clear winner with purpose-built AI features that Make and Zapier cannot match.

Hybrid Approach: Use Make/Zapier for general automation + Draft’n Run for AI workflows.

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Related Comparisons & Resources

More Platform Comparisons:

• Draft’n Run vs n8n - AI-first vs general automation
• Draft’n Run vs AirOps - AI workflow platform comparison
• Lang Chain vs AutoGPT - AI framework comparison
• CrewAI vs LangChain - Multi-agent frameworks

Alternative Platform Guides:

• Zapier Alternatives - Best Zapier alternatives for AI
• Make Alternatives - Make (Integromat) alternatives
• n8n Alternatives - Complete n8n alternatives guide
• LangChain Alternatives - LangChain alternatives

Draft’n Run Platform:

• AI Workflow Builder - Visual workflow builder
• AI Chatbot Platform - Build production AI chatbots
• AI Automation - End-to-end automation
• Integration Library - 100+ integrations
• Templates - Ready-to-deploy workflows
• Pricing - Transparent pricing
• Request Demo - See it in action