Webinar: Why fragmented RAG stacks hit limits (and what to do instead)

​Most production agent architectures combine relational state, graph relationships and vector retrieval across separate systems. That flexibility comes with trade-offs: different consistency models, extra round trips, and more application logic to keep everything aligned.

​In this session, Matthew will show where that complexity starts to affect retrieval quality and operational reliability, especially when filtering, ranking and relationship context live in different places. He’ll then walk through an alternative approach: keeping graph, documents, vectors and state in one engine, so teams can simplify the stack and improve accuracy.

​Speaker

​Matthew Penaroza
(Head of AI Solution Architecture, SurrealDB)

​​Matthew Penaroza is Head of Solution Architecture at SurrealDB, where he helps design and scale distributed AI systems for global enterprises. As the solutions architect behind the core database systems at companies such as Plaid, Uber, and Atlassian, he brings firsthand insight into how the world’s largest organizations design data infrastructure and how those same architectural principles can be applied to AI systems that demand context precision and intelligent data management.

​Joining the webinar

​Once you register, you'll get an email from SurrealDB with your personal join link. Hold onto it - that's your ticket in.