In this post, we continue our AI journey with SQL Server 2025 (Preview). In previous articles, I already showed how to call the GPT-4o chat-completion model in Azure directly from SQL Server to generate product descriptions, how to create and store embeddings for semantic search, and how to use the (preview) acceleration features for semantic search workloads. If you want…
Introduction In the first part of this RAG series, we established the fundamentals of Naive RAG with dense vector embeddings on PostgreSQL using pgvector. That foundation works well for conceptual queries, but production systems quickly reveal a limitation: pure semantic search misses exact matches like you would have with like or Full-text searches. When someone searches for “PostgreSQL 17 performance…
Introduction Nowadays, everyone in IT is well versed in using ChatGPT and other LLM-powered Chat to retrieve information like Google or try to learn something with it. The problem with those models is their accuracy. Current AI models only know what information they have been fed and expose it to you in a format you understand (which is already surprisingly…
