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Wednesday, January 21 at 8:00 PM GMT

Webinar

Vector RAG that actually understands context

Basic vector RAG breaks down as systems scale. Semantic similarity alone cannot enforce hierarchy, causality, or typed relationships - leading to degraded accuracy and opaque results over time.

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About this webinar

In this live webinar, Matthew Penaroza (Head of Solutions Architecture, SurrealDB) shows how to design retrieval systems that maintain context as data and usage grow. You’ll learn how vectors and graphs work together to enforce structure, reduce search space, and explain why evidence was retrieved - not just that it was. This session focuses on retrieval quality and interpretability, not database internals.

Speakers

Matthew Penaroza

Matthew Penaroza

Head of Solution Architecture at SurrealDB

In this session you'll learn

Why vector-only RAG fails at scale (and why common fixes don’t solve it)

What “context” actually means in retrieval systems

How graph-based retrieval complements vectors

Implementing hybrid vector + graph retrieval in a single query

Producing retrieval traces that explain evidence selection

What to measure to avoid semantic collapse in production

SurrealDB

The context layer for AI agents.

Documents, graphs, vectors, time-series, and memory - in one transaction, one query, one deployment.

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