LaunchedEditorial Listing

Semantic Kernel

Microsoft · Model-Agnostic AI Agent SDK

Open Semantic Kernel

A Microsoft SDK for building, orchestrating, and deploying AI agents and multi-agent systems in .NET, Python, and Java.

PricingFree

Setupmedium

Runs onSelf-hosted

APINo

Open sourceYes

DocsYes

CategoryAgent Frameworks

Agent Framework.NETPythonJavaOpen SourceMicrosoft

Best for

Adding AI agents to .NET, Python, and Java apps

Not ideal for

Non-developers or teams outside the Microsoft ecosystem

Who it's for

Enterprise developers integrating AI agent capabilities into .NET, Python, or Java applications

Capabilities

Multi-language support: .NET, Python, and Java
Model-agnostic — works with cloud, local, and custom models
Enterprise-grade observability and security
Multi-agent orchestration capabilities
100+ samples and extensive Microsoft Learn documentation

Limitations

Requires developer expertise in .NET, Python, or Java
No hosted deployment — integrates into your own applications
Strongest in the Microsoft / Azure ecosystem
Less focused on agent UX patterns than higher-level frameworks

Use cases

Adding AI agent capabilities to existing enterprise applications
Building multi-agent systems in .NET or Java environments
Integrating local and cloud LLMs into production software
Enterprise AI workflows with security and compliance requirements
Prototyping agent-powered features in polyglot codebases

Integrations & fit

Azure OpenAIOpenAIOllama.NETPythonJava

Good fit forStartup / small team, Enterprise

Pricing modelFree· No cost to start

See pricing on Semantic Kernel →

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About Semantic Kernel

Semantic Kernel is an open-source, model-agnostic SDK by Microsoft that enables developers to integrate AI agent capabilities into applications written in .NET, Python, or Java. It supports building everything from simple chatbots to complex multi-agent workflows, with enterprise-grade features including observability, security, and flexible model integration. Semantic Kernel works with cloud-based models (Azure OpenAI, OpenAI), local models (Ollama, LMStudio, ONNX), and custom integrations. The SDK is MIT-licensed, self-hosted, and designed to slot into existing enterprise application architectures rather than requiring a standalone deployment. Microsoft maintains the project actively with over 100 samples and comprehensive documentation on Microsoft Learn.

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