DataStax announced a milestone in its journey to simplify enterprise retrieval-augmented generation (RAG) for developers by integrating with Microsoft Semantic Kernel. This integration enables developers to more easily build RAG applications and vectorize data with Astra DB and Microsoft's ecosystem of AI products and copilots using Semantic Kernel?s open source SDK for AI applications and agents. DataStax has integrated Astra DB as a vector database with Microsoft's open source Semantic Kernel so that any C#, Python, or full-stack application developers can more easily build RAG applications and AI agents that use their enterprise data using Semantic Kernel?s unique features for managing contextual conversations, multi-step functions and connections with the Microsoft AI ecosystem.

Semantic Kernel is a highly extensible open-source SDK that lets developers easily build agents that can call to existing code and can be used with orchestration models like OpenAI, Azure OpenAI, GitHub CoPilot, and Hugging Face. Key features of Semantic Kernel include semantic functions, chaining capabilities, planners, and connectors for various enterprise applications and data sources. Integrating these features with Astra DB adds the power of a vector database that provides both vector and structured data with high relevancy, ultra-low latency, and global-scale to AI applications and agents built leveraging Semantic Kernel.