·작성자 AI Resource Hub Team
AI 워크플로 오케스트레이션: Dify, LangFlow, Flowise 등
복잡한 AI 파이프라인을 설계, 배포 및 관리하기 위한 로우코드 AI 워크플로 빌더 비교.
Why Orchestrate AI Workflows?
Building AI applications involves chaining prompts, tools, APIs, and logic. Workflow orchestration platforms make this visual and maintainable.
Dify
- Type: Open-source with cloud option.
- Strengths: Full-featured — RAG, agents, workflows, prompt management.
- Best for: Teams wanting an all-in-one platform.
- Pricing: Free self-hosted, cloud from $59/month.
LangFlow
- Type: Open-source, Python-based.
- Strengths: Visual builder for LangChain pipelines.
- Best for: Developers already using LangChain.
- Pricing: Free self-hosted.
Flowise
- Type: Open-source, Node.js-based.
- Strengths: Drag-and-drop LLM flow builder.
- Best for: Quick prototyping of chatbots and RAG.
- Pricing: Free self-hosted.
n8n + AI Nodes
- Type: Open-source workflow automation.
- Strengths: Connect AI to 300+ integrations.
- Best for: Business automation with AI steps.
- Pricing: Free self-hosted, cloud from €20/month.
Comparison
| Feature | Dify | LangFlow | Flowise | n8n |
|---------|------|----------|---------|-----|
| Visual editor | ✓ | ✓ | ✓ | ✓ |
| RAG built-in | ✓ | ✓ | ✓ | ✗ |
| Agent support | ✓ | ✓ | ✓ | ✓ |
| API deployment | ✓ | ✓ | ✓ | ✓ |
| Self-hosted | ✓ | ✓ | ✓ | ✓ |
When to Use Code Instead
- Complex business logic that's hard to express visually.
- Performance-critical paths where overhead matters.
- Custom model training or fine-tuning pipelines.
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