Semantic Kernel
Bot platforms software
Natural language generation (NLG) software
Natural language understanding (NLU) software
AI code generation software
Generative AI infrastructure software
Conversational intelligence software
Natural language processing (NLP) software
Generative AI software
- Features
- Ease of use
- Ease of management
- Quality of support
- Affordability
- Market presence
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What is Semantic Kernel
Semantic Kernel is an open-source SDK for building applications that orchestrate large language models with tools, plugins, memory, and prompt templates. It targets software developers who need to embed generative AI into products such as assistants, copilots, and workflow automations. The project focuses on application-layer orchestration (function calling, planning, and connectors) rather than providing a hosted chatbot service. It supports common programming environments (notably .NET and Python) and is typically used alongside external model providers and vector databases.
Open-source orchestration SDK
Semantic Kernel provides a developer-focused framework for composing prompts, functions, and tool integrations into repeatable AI workflows. Because it is open source, teams can inspect the code, self-host, and adapt components to internal standards. This is useful for organizations that want more control than packaged bot platforms while still using a structured framework.
Plugin and tool integration model
The SDK includes a plugin abstraction that helps developers expose application capabilities (APIs, functions, data access) to an LLM-driven workflow. This supports common assistant patterns such as tool calling, retrieval-augmented generation, and multi-step task execution. It is designed to integrate with external services rather than replacing them.
Strong .NET ecosystem alignment
Semantic Kernel is well-aligned with .NET development practices and integrates naturally into C# application architectures. This lowers adoption friction for teams building AI features in Microsoft-centric stacks. It also supports Python, enabling cross-language prototyping and service implementations.
Not a turnkey bot platform
Semantic Kernel is an SDK, not a hosted conversational platform with built-in channels, inbox, routing, or agent management. Teams must build and operate the surrounding application, UI, and deployment infrastructure. Organizations seeking out-of-the-box customer chat operations may need additional products or custom development.
Requires external model providers
The SDK does not include proprietary foundation models; it relies on integrations with third-party model APIs or self-hosted models. Cost, latency, data residency, and availability depend on the chosen model provider and hosting approach. This can complicate procurement and production operations compared with fully managed offerings.
Evolving APIs and patterns
As an actively developed open-source project, some abstractions and recommended patterns can change over time. Teams may need to track releases, update code, and validate behavior across model/provider updates. This can increase maintenance effort for long-lived enterprise implementations.
Plan & Pricing
| Plan | Price | Key features & notes |
|---|---|---|
| Open-source (MIT) | Free | Semantic Kernel is an open-source SDK distributed under the MIT license. There are no vendor subscription plans or paid tiers for the SDK itself. Costs for running applications built with Semantic Kernel arise from the external AI services you connect (e.g., Azure OpenAI, OpenAI) and any cloud infrastructure you provision. |
Seller details
Microsoft Corporation
Redmond, Washington, United States
1975
Public
https://www.microsoft.com/
https://x.com/Microsoft
https://www.linkedin.com/company/microsoft/
