Semantic Kernel
SDK for integrating and orchestrating AI models with conventional programming languages.
🛡️ AgentReady threat assessment
MAESTRO 7-layer threat model + OWASP AIVSS risk score for Semantic Kernel, derived from its capabilities.
These scores are auto-generated from public information (the agent's own listing, docs, and repository) using the canonical OWASP AIVSS formula and the MAESTRO framework — an estimate for guidance, not a penetration test, audit, or certification. See the scoring methodology — every score is re-derived by the same automated method as an agent's public evidence changes.
Overview
Semantic Kernel is an open-source SDK that enables developers to integrate AI capabilities from various services like OpenAI, Azure OpenAI, and Hugging Face into existing applications. It provides abstractions to simplify working with different AI models, improve reliability, and create controlled user experiences through fine-tuned prompts and task planning.
Key features and capabilities
- Kernel as a central dependency injection container
- Connectors for various AI services and data sources
- Plugin system for encapsulating functions
- Planner for orchestrating execution strategies
- Memory abstractions for context management
- Support for multiple programming languages (C#, Java, Python)
Use cases
- Building AI-powered chatbots and conversational agents
- Integrating AI capabilities into existing enterprise applications
- Creating automated AI function chains for complex tasks
- Developing scalable AI applications with incremental capabilities
- Orchestrating multi-step AI workflows