DeepYard

Rasa vs Semantic Kernel

Side-by-side comparison built from DeepYard's structured catalog. Content updated Aug 21, 2026.

Direct Answer

Rasa suits teams needing freemium $35, conversational ai focus, and 21,301 GitHub stars in current listing data. Semantic Kernel suits teams needing open-source access, csharp focus, and 28,477 GitHub stars in current listing data. This summary reflects catalog metadata only for decision support, not independent testing.

What this comparison weighs

  • Pricing and free-tier availability
  • License model and deployment fit
  • GitHub adoption and contributor depth
  • Catalog tags, integrations, and supported workflows
R

Rasa

On-premise conversational AI framework for enterprise virtual assistants

OSSfreemium
21.3K400.0K/w4w ago298
S

Semantic Kernel

Microsoft's SDK for integrating LLMs into applications — 24K+ stars

OSSFree
28.5Ktoday400
MetricRasaSemantic Kernel
GitHub Stars21.3K28.5K
Contributors298400
Last CommitJul 24, 2026Aug 21, 2026
Open Issues153250
Licenseopen-sourceopen-source
Pricingfreemiumopen-source
Free TierYesYes
Categoryframeworksframeworks
TrendingNoNo

Choose Rasa if you need

  • Rasa is the stronger pick when Conversational Ai matters because that capability is listed only on its profile.
  • Rasa is the cleaner fit if you specifically need Conversational Ai workflows from the catalog tags.

Choose Semantic Kernel if you need

  • Semantic Kernel stands out for Csharp workflows that are not listed for Rasa.
  • Semantic Kernel is the stronger pick when Multi Agent matters because that capability is listed only on its profile.
  • Semantic Kernel shows broader GitHub adoption with 28,477 stars versus 21,301 for Rasa.

Meaningful differences

  • Pricing model: Rasa is listed as freemium from From $35K/yr (Enterprise), while Semantic Kernel is listed as open-source.
  • Workflow emphasis: Rasa highlights Python, while Semantic Kernel highlights Csharp.
  • GitHub adoption: Rasa shows 21,301 stars versus 28,477 for Semantic Kernel.
  • Contributor count: Rasa lists 298 contributors and Semantic Kernel lists 400.

Shared capabilities

  • Enterprise
  • Python
  • Open Source

Shared Tags

enterprisepythonopen-source

Only in Rasa

conversational-aion-premisenlu

Only in Semantic Kernel

microsoftcsharpjavamulti-agentplugins

Limitations and evidence

  • DeepYard compares structured public metadata; this is not an independent benchmark unless a test record is shown.
  • Signals such as stars, contributors, and last commit indicate public activity, not purchase fit or runtime quality.
  • Pricing and feature coverage reflect the stored listing snapshot and may lag vendor changes between refreshes.

About Rasa

Rasa is an open-source conversational AI framework for building enterprise-grade virtual assistants and chatbots. It provides NLU, dialogue management, and LLM integration with full on-premise deployment support. Rasa focuses on regulated industries that need data privacy, compliance, and control over their AI infrastructure.

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About Semantic Kernel

Semantic Kernel is Microsoft's open-source SDK for building AI agents and integrating LLMs into enterprise applications. It supports C#, Python, and Java with a plugin architecture for extending agent capabilities. Semantic Kernel provides planning, memory, and function-calling abstractions that work with OpenAI, Azure OpenAI, and Hugging Face models.

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