Building and Evaluating RAG Pipelines

Retrieval-Augmented Generation (RAG) pipelines are essential for building intelligent chatbots that can provide accurate, context-rich responses. Turning this concept into a working application requires hands-on experience with tools, techniques, and evaluation methods. In this session, you’ll bring it all together by building a real-world AI chatbot designed to answer questions about the New York Stock Exchange.

In this session, Abi Aryan, Founder at Abide AI, will walk you through how to build a RAG-powered chatbot using Python. You’ll learn how to construct the RAG pipeline, evaluate response quality, and apply it to real-world use cases. This session is ideal for AI engineers who want to deepen their RAG skills with a practical, high-value application.

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