Build intelligent AI agents and applications with Microsoft’s open-source AI development framework.
Website
Category
AI Agent Builders
Pricing
Free & Open Source
Overview
Semantic Kernel is an open-source AI development framework from Microsoft that helps developers build AI-powered applications, intelligent agents, and multi-agent systems. It provides the tools needed to connect large language models with application code, APIs, plugins, data sources, and business logic.
Designed primarily for developers and technical teams, Semantic Kernel provides a flexible foundation for creating AI agents that can understand instructions, call functions, use external tools, maintain context, and participate in more complex automated workflows.
The framework supports C#, Python, and Java, making it suitable for organizations that want to incorporate generative AI and agentic capabilities into existing software applications without being locked into a single programming language or AI model provider.
Tool Information
| Field | Details |
|---|---|
| Name | Semantic Kernel |
| Category | AI Agent Builders |
| Type | Open-Source AI Development Framework |
| Developer | Microsoft |
| Deployment | Self-Hosted / Application-Based |
| Platform | C#, Python, Java |
| AI Agents | Yes |
| Multi-Agent Systems | Yes |
| Plugin Support | Yes |
| Function Calling | Yes |
| Workflow Orchestration | Yes |
| Open Source | Yes |
| Official Website | https://learn.microsoft.com/en-us/semantic-kernel/ |
Key Features
AI Agent Development
Build intelligent agents that can interact with users, follow instructions, use tools, and perform tasks.
Capabilities
- AI agent creation
- Agent instructions
- Tool usage
- Function calling
- Conversation management
- Autonomous task execution
Multi-Agent Orchestration
Coordinate multiple specialized AI agents to work together on complex tasks and workflows.
Features
- Sequential workflows
- Concurrent agent execution
- Agent handoffs
- Group conversations
- Multi-agent collaboration
- Specialized agent roles
Plugins & Function Calling
Connect AI agents to existing application functionality, APIs, and business systems.
Capabilities
- Custom plugins
- Native code functions
- API connections
- Function calling
- External tool integration
- Business logic integration
AI Model Integration
Connect applications with different AI model providers and services.
Advantages
- Flexible model selection
- Multiple AI service options
- Model provider abstraction
- Easier model switching
- Integration with existing AI infrastructure
Enterprise AI Development
Build AI applications that can integrate with existing enterprise software and development environments.
Benefits
- Modular architecture
- Application monitoring
- Telemetry
- Middleware support
- Extensible components
- Production-oriented development
Human-in-the-Loop Workflows
Allow human users to participate in AI-powered workflows when approval, review, or decision-making is required.
Use Cases
- Approval processes
- Agent supervision
- AI-assisted decisions
- Human-agent collaboration
- Business process review
Use Cases
AI Agents
Develop customized AI agents capable of interacting with users and using connected tools to complete tasks.
Enterprise AI Applications
Add generative AI and agentic functionality to existing business applications and software systems.
Multi-Agent Systems
Create teams of specialized AI agents that collaborate to solve more complex problems.
Business Process Automation
Combine AI models, application logic, and external tools to automate multi-step business processes.
AI Assistants
Build domain-specific assistants that can access business information and perform actions through connected functions.
Custom Copilots
Develop customized AI copilots for internal teams, customers, developers, and specialized business workflows.
How Semantic Kernel Works
Semantic Kernel acts as an orchestration layer between AI models, application code, plugins, and external services.
Typical Workflow
- Choose an AI model or service
- Create a Semantic Kernel application
- Add plugins and functions
- Configure an AI agent
- Define instructions and goals
- Connect external tools and APIs
- Execute tasks or agent workflows
- Monitor and improve the application
For more advanced applications, developers can use multi-agent orchestration patterns to coordinate several specialized agents and divide complex tasks between them.
Integrations
Supported Workflows
- OpenAI
- Azure OpenAI
- Anthropic
- Google AI services
- Custom AI services
- REST APIs
- OpenAPI-based services
- Application code
- External tools
- Enterprise systems
Advantages
- Open-source framework
- Developed by Microsoft
- Supports C#, Python, and Java
- Dedicated AI agent capabilities
- Multi-agent orchestration
- Plugin architecture
- Function calling
- Flexible AI model integration
- Enterprise-focused development
- Supports human-in-the-loop workflows
- Suitable for custom AI applications
Limitations
- Primarily designed for developers and technical teams
- Requires programming knowledge
- Building advanced agents can require significant development work
- Complex multi-agent systems can require careful architecture
- Some advanced agent and orchestration capabilities may evolve as the framework develops
Pricing
Free & Open Source
Semantic Kernel is available as an open-source framework and does not require a software license fee.
Additional AI & Infrastructure Costs
Although Semantic Kernel itself is free, applications built with it may require separate costs for AI model APIs, cloud infrastructure, databases, hosting, and other external services.
Visit the official website for the latest information.
Company Information
| Field | Details |
|---|---|
| Product Name | Semantic Kernel |
| Company | Microsoft |
| Category | AI Agent Builders |
| Industry | Artificial Intelligence |
| Product Type | Open-Source AI Development Framework |
| Deployment | Self-Hosted / Application-Based |
| Target Audience | Developers, AI Engineers, Software Teams, Enterprises |
| Official Website | https://learn.microsoft.com/en-us/semantic-kernel/ |
Frequently Asked Questions
What is Semantic Kernel?
Semantic Kernel is Microsoft’s open-source framework for building AI-powered applications, AI agents, and multi-agent systems.
Who should use Semantic Kernel?
Semantic Kernel is primarily designed for developers, AI engineers, software teams, and enterprises building customized AI applications and agentic workflows.
Does Semantic Kernel require coding?
Yes. Semantic Kernel is a developer-focused framework, so programming knowledge is generally required to build applications with it.
Which programming languages does Semantic Kernel support?
Semantic Kernel supports C#, Python, and Java.
Can Semantic Kernel build multi-agent systems?
Yes. Semantic Kernel provides agent orchestration capabilities that allow multiple specialized AI agents to collaborate on complex tasks.
Is Semantic Kernel free?
Yes. Semantic Kernel is open source and can be used without paying a software license fee. However, external AI models, APIs, hosting, and infrastructure may have separate costs.
