Virtual Event

Build GenAI Apps with RAG: Master Vector Storage and Search

This livestream will show you how to build a visual GenAI workflow powered by a vector database for seamless vector storage and search. You’ll learn to create a real-time Retrieval Augmented Generation (RAG) pipeline that enhances LLMs with domain-specific knowledge.

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Large Language Models (LLMs) are smart, but they don’t know your domain. This livestream will show you how to build a visual GenAI workflow powered by a vector database for seamless vector storage and search. You’ll learn to create a real-time Retrieval Augmented Generation (RAG) pipeline that enhances LLMs with domain-specific knowledge.

Using GitHub, Codespaces, and GitHub Copilot, we’ll build a fully functional GenAI app that grows smarter as your data evolves. Discover how to level up your GenAI projects with tools that make development faster, smarter, and more efficient.

During this session, you’ll learn how to:

  • Build smarter workflows: Learn how to create a visual GenAI workflow with seamless vector storage and search.
  • Enhance LLMs with your data: Develop a real-time RAG pipeline to give LLMs domain-specific knowledge.
  • Leverage powerful tools: See how GitHub, Codespaces, and GitHub Copilot streamline your GenAI app development.
  • Create evolving applications: Build a GenAI app that adapts and learns as your data grows.


David Jones-Gilardi

David Jones-Gilardi

Developer Relations Engineer