Dust vs Semantic Kernel
A detailed comparison to help you choose between Dust and Semantic Kernel.
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How to choose
Neither tool has user reviews on ToolSpotter yet, so we don't pick a winner. Compare them on what they're built for: Dust — Enterprise teams building custom AI knowledge assistants; Semantic Kernel — Enterprise developers building production AI agents that need structured orchestration, multiple LLM support, and integration with existing enterprise systems..
Dust Custom AI assistants powered by your data | Semantic Kernel Microsoft's orchestration framework for building AI agents with LLMs | |
|---|---|---|
| Rating | Not yet rated | Not yet rated |
| Pricing Model | paid | free |
| Starting Price | From $29/mo | Free |
| Best For | Enterprise teams building custom AI knowledge assistants | Enterprise developers building production AI agents that need structured orchestration, multiple LLM support, and integration with existing enterprise systems. |
| Free Tier | ||
| API Access | ||
| Team Features | ||
| Open Source | ||
| Tags | team featuressso | free tieropen sourceapi access |
| Visit Dust → | Visit Semantic Kernel → |
Dust
Pros
- + Deep data source integrations
- + Team knowledge sharing
- + Custom assistant marketplace
Cons
- - Premium pricing
- - Limited free testing
Semantic Kernel
Pros
- + Integrate multiple LLM providers through a single interface
- + Define custom plugins and functions for AI agents to call
- + Built-in memory and context management for multi-turn interactions
- + Strong Microsoft ecosystem integration (Azure, Copilot)
- + Active open-source development with regular updates
Cons
- - Steeper learning curve compared to simpler LLM libraries
- - C# support more mature than Python implementation
- - Requires managing your own LLM API keys and costs
Frequently Asked Questions
Which is better, Dust or Semantic Kernel?▼
It depends on your specific needs — neither tool has user reviews on ToolSpotter yet, so we don't rank one above the other. Dust is best for: Enterprise teams building custom AI knowledge assistants. Semantic Kernel is best for: Enterprise developers building production AI agents that need structured orchestration, multiple LLM support, and integration with existing enterprise systems..
What is the difference between Dust and Semantic Kernel?▼
Dust: Dust connects company knowledge and tools so teams can build and share AI agents that work inside real workflows, using different models per task. Semantic Kernel: Semantic Kernel is Microsoft's open-source SDK for building AI agents, letting an application call models, plugins and its own functions from C#, Python or Java.
Is Dust or Semantic Kernel more affordable?▼
Dust starts at €29/mo, Semantic Kernel starts at €0/mo. Check the comparison table above for current pricing.
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