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How to build a GenAI Application with Vectara - a Step-by-Step Guide

Ofer Mendelevitch Ofer Mendelevitch | Head of Developer Relations | Vectara

Building a Gen AI enterprise product may seem easy at first, but when you need to consider scalability, security and upgrades in an enterprise production environment - things can get complicated pretty quickly. In this talk I will explain what retrieval augmented generation (RAG) is, how it helps reduce hallucinations, and why Vectara's RAG-as-a-service approach makes it easy to build a GenAI application at enterprise scale.  I will show how to build a RAG application with Vectara step-by-step, using data from Richard Feynman's lectures on physics, and how tools like vectara-ingest and React-chat can help accelerate your success.

Ofer Mendelevitch
Ofer Mendelevitch
Head of Developer Relations | Vectara

Ofer Mendelevitch leads developer relations at Vectara. He has extensive hands-on experience in machine learning, data science and big data systems across multiple industries, and has focused on developing products using large language models since 2019. Prior to Vectara he built and led data science teams at Syntegra, Helix, Lendup, Hortonworks and Yahoo! Ofer holds a B.Sc. in computer science from Technion and M.Sc. in EE from Tel Aviv university, and is the author of "Practical data science with Hadoop" (Addison Wesley).