Introducing our new University course: “SurrealDB for AI Engineers”

SurrealDB University has launched “SurrealDB for AI Engineers,” a free, hands-on eleven-lesson course designed to teach developers how to build the retrieval, memory, and context layers used in modern AI applications. The curriculum covers AI and context engineering fundamentals, vector and full-text search, RAG knowledge bases, hybrid search with reranking, agent memory, text-to-SurrealQL, secure multi-agent context-layer architecture, document chunking, retrieval evaluation, and multi-hop Graph RAG. Built for practical learning, the course requires no prior SurrealDB experience, cloud account, or embedding API, and has students run SurrealDB locally through schemas, datasets, and queries that expose retrieval mechanics. Its progression reflects the development of AI systems from basic semantic RAG toward applications requiring keyword search, structured filters, relationships, persistent memory, permissions, and access to varied data sources, using SurrealDB’s combined structured, document, graph, vector, and full-text capabilities.

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