Paula Santamaría
Software Architect @ Serenity Star
Paula Santamaría is a Software Architect specializing in .NET. She currently leads the architecture of Serenity* Star, defining the technical aspects of features in collaboration with Product Design. In her role, she also conducts code reviews and guides teams on best practices and design patterns.
Previously, she worked as a .NET Software Architect contractor, leading the development of internal frameworks used across teams to improve engineering practices.
She holds a degree in IT Management and began coding in high school, later entering the software industry full-time in 2012. Since then, she has built systems across a wide range of domains. She is also the author of TypeScript Gamified and the winner of the 2021 GitHub Actions Hackathon.
POSETTE 2026 Talk
Production RAG at Scale with Azure Database for PostgreSQL
One of PostgreSQL's greatest strengths is its ability to serve as more than just a traditional database—it can be the foundation for intelligent systems. With the rise of AI-powered applications, PostgreSQL has emerged as a powerful platform for Retrieval-Augmented Generation (RAG) implementations. So, why should we consider PostgreSQL over specialized vector databases for production RAG systems?
In this talk, we'll explore a complete production RAG architecture that powers Serenity Star's enterprise knowledge management platform. With features like pgvector for semantic search, DiskANN for high-performance indexing, and seamless integration with Microsoft Semantic Kernel, PostgreSQL proves itself as a robust foundation for intelligent knowledge systems processing millions of queries monthly.
Drawing from our real-world experience as Azure customers scaling RAG from prototype to production, we will share practical insights on architecture decisions, performance optimization strategies, and monitoring approaches. We'll cover the complete pipeline: from document chunking and vector storage to semantic search optimization and production monitoring and observability.
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