Semantic Kernel

Sweet spot: a Microsoft-house enterprise where .NET or Java is the primary language and Azure is the cloud. For that profile, Semantic Kernel removes every friction point — SSO, governance, existing tooling, data residency — that Python-first frameworks would force you to retrofit. Microsoft ships it because Microsoft customers demanded a serious orchestration framework in their stack. Failure modes. If you are a Python-native team with no Microsoft ecosystem investment, Semantic Kernel's Python SDK will feel like a second-class citizen to LangChain / LangGraph. Documentation quality varies sharply: the C# .NET content is excellent; the Java and Python content is uneven. And the Agent Framework, while capable, trails LangGraph in community adoption, meaning fewer third-party tutorials. What to pilot. Build one agent that touches your existing Microsoft identity and data estate — an Entra-authenticated tool over a SharePoint doc set, for example. If the framework handles auth, observability, and governance gracefully, it is the right match; if you end up fighting it, a Python-first framework will serve you better even with the ecosystem-mismatch tax.

Semantic Kernel is Microsoft's open-source SDK for integrating LLMs into conventional software. It provides a unified abstraction for models, a plugin model for tools, an agent framework with group chat patterns, memory and RAG primitives, filters (think middleware for LLM calls), and planners that turn a goal into a sequence of plugin invocations. The differentiator versus LangChain / LangGraph is language breadth. Semantic Kernel has full-quality SDKs for C#, Python, and Java — a rare trio — which makes it the default choice for enterprise shops already on .NET or the JVM. It also integrates tightly with the broader Microsoft ecosystem: Azure OpenAI, Azure AI Search, Azure AI Foundry, Microsoft 365 Copilot extensibility, Entra ID auth. The Agent Framework (integrated in 2024) brings LangGraph-style multi-agent workflows: orchestrator agents, group chat, handoff patterns, and a process framework for durable long-running flows. A new Process Framework added in 2025 handles saga-style durable workflows across systems. Used heavily inside Microsoft (for Copilot extensibility) and in enterprise .NET / Java shops. Open source (MIT), model-agnostic, and actively released every few weeks.