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Video of a conference talk that will show you how to revolutionize your applications using the Graph-Based RAG on PostgreSQL. The talk will show using PostgreSQL with vector and graph data to enable natural language queries for highly accurate results that will power your RAG application.
Vector data will be explained as a tool that enhances PostgreSQL’s ability to manage information for GenAI apps. The session explores how to integrate graph, and vector data using azure_ai, pg_diskann, age and pgvector extensions. As well as advanced techniques to improve accuracy of results and improve vector search performance at scale.
A hands-on demonstration will show how to set up PostgreSQL to handle these types of queries, store vector data, and create queries that respond to natural language inputs. A practical example will involve building a legal copilot to help lawyers find relevant legal cases during research.
Participants will leave the session equipped to apply similar graph, indexing and vector features in their own applications, making them more intuitive, user-friendly and scalable.
Abe Omorogbe is an experienced AI professional with nearly a decade in the field. At Microsoft, he develops cutting-edge Data + AI products, focusing on PostgreSQL and previously serving as Lead PM for LLMOps/MLOps on Azure AI. Before rejoining Microsoft, Abe worked at Databricks, where he enhanced his expertise in AI and machine learning as Lead PM for MLflow. He is passionate about using AI to tackle complex challenges and drive innovation.
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► Video bookmarks:
00:00 Introduction
01:47 Agenda / Why Postgres
03:47 US Case Law Dataset
04:32 Semantic Search
05:37 Vector 101
08:25 Basic RAG
09:09 Common Problem with RAG
13:45 Advanced RAG Architecture
20:40 Resources
Everything you need to know about POSETTE: An Event for Postgres 2025 can be found at: https://posetteconf.com
Learn more:
Watch more POSETTE talks: https://aka.ms/posette-playlist
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