Haystack vs Semantic Kernel
Agent-Assisted
A modular, production-ready framework for building agentic AI systems with context engineering and customizable building blocks.
Agent-Assisted
A Microsoft framework for building AI applications that orchestrates interactions between large language models and native code through semantic functions and plugins.
Summary
- Haystack scores 3.6/5 and Semantic Kernel scores 3.7/5 on the Dark Factory Score, a difference of 0.1.
- The widest gap is Integration: Haystack 3.5, Semantic Kernel 4.5.
- Semantic Kernel scores higher on integration.
- They score the same on autonomy, code quality, self-correction and project complexity.
- Both are listed as open source.
- Both are listed under Agent Frameworks, Orchestration and Full-Stack Agents.
Dimension by dimension
| Dimension | Weight | Haystack | Semantic Kernel |
|---|---|---|---|
| Autonomy | 28% | 3.5 | 3.5 |
| Code Quality | 20% | 4.0 | 4.0 |
| Integration | 17% | 3.5 | 4.5 |
| Self-Correction | 15% | 2.5 | 2.5 |
| Project Complexity | 20% | 4.0 | 4.0 |
| Dark Factory Score | 3.6 | 3.7 |
Why Haystack scores 3.6
Haystack is a mature, production-ready framework specifically designed for building agentic AI systems with strong modular architecture. Its emphasis on 'modular and customizable building blocks' and production-readiness suggests excellent code quality and structured output. The framework's focus on context engineering and agentic systems indicates good autonomy capabilities, allowing for multi-step AI workflows. The extensive documentation, tutorials, cookbook, and enterprise offerings demonstrate solid integration capabilities with established deployment patterns.
Scored by Claude AI — last evaluated February 27, 2026
Why Semantic Kernel scores 3.7
Semantic Kernel is a sophisticated orchestration framework that excels at integrating AI capabilities into applications through its plugin architecture and semantic functions. It provides strong code quality features with comprehensive documentation, TypeScript support, and production-ready patterns for building AI applications. The framework's Microsoft backing ensures enterprise-grade reliability and extensive integration capabilities with Azure services, CI/CD pipelines, and existing codebases. Its modular design allows developers to compose complex AI workflows and manage multi-step interactions between LLMs and native code effectively.
Scored by Claude AI — last evaluated February 27, 2026
More comparisons
Generated from Dark Factory Score data. How the score works. Comparing three or more tools at once is part of Pro.