Framework Comparison
Compare popular agentic AI frameworks and find the perfect fit for your project
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0 / 5 completedThe Framework Landscape
The agentic AI ecosystem offers several powerful frameworks, each with unique strengths and trade-offs. Choosing the right one depends on your use case, team experience, and technical requirements.
Interactive: Explore Frameworks
LangChain
The Swiss Army Knife
✓ Strengths:
- •Comprehensive ecosystem
- •Extensive integrations
- •Strong RAG support
- •Large community
✗ Weaknesses:
- •Steep learning curve
- •Can be heavyweight
- •Frequent API changes
Best For:
RAG applications, document processing, multi-step chains
🏢 Enterprise
Need Azure integration, .NET support, and enterprise features?
→ Semantic Kernel
🔍 Search & RAG
Building document Q&A or search systems?
→ LangChain or Haystack
👥 Multi-Agent
Need agents to collaborate and communicate?
→ AutoGen
🎯 Key Decision Factors
- •Use Case: RAG, multi-agent, code generation, or custom workflow?
- •Tech Stack: Python, .NET, or language-agnostic?
- •Team Experience: Learn new framework or use familiar tools?
- •Production Needs: Performance, scalability, support requirements?