This collection highlights the application and advantages of vector search technologies across various fields, including generative AI and data management. Topics include retrieval augmented generation, comparison of search methods, integration with databases like Azure Cosmos DB and Redis, and handling unstructured data through machine learning embeddings. Key documents discuss semantic search applications, the significance of vector databases in enhancing search capabilities, and improvements to query processing, showcasing real-world implementations and techniques for optimizing AI-driven solutions.
Building Enterprise Agents with Azure AI Search: From RAG to Agentic Retrieval