Semantic Kernel is an artificial intelligence orchestration framework designed to integrate large language models with existing codebases. It functions as an agentic workflow engine, providing a standardized interface that connects generative models to traditional application logic, data sources, and external tools to automate complex, multi-step business tasks.
The platform distinguishes itself through a modular plugin architecture and a planner-based reasoning engine that decomposes high-level goals into executable sequences of functions. By utilizing a connector-based abstraction layer, it decouples core orchestration logic from specific model providers and vector databases, allowing for consistent retrieval and execution across diverse infrastructure.
The framework includes a middleware-based request pipeline for managing cross-cutting concerns such as telemetry and safety filtering, alongside a prompt template engine for dynamic context injection. These components support the development of scalable, enterprise-ready systems that maintain security and compliance while coordinating multiple language models and specialized tools.
