Building an Enterprise-Grade Agentic RAG

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Agents, optimum context-based chunking, and specialized RAGs/LLMs with large context window and knowledge graphs, based on enterprise corpuses, are showing promising results. It is a topic of very active research with new articles and products released almost weekly, leveraging the latest technology. If you want to learn what it is about, and build your own scalable, secure version for your needs, using the best solutions on the market, I highly recommend attending this session.

Overview

Join us for an in-depth technical webinar on building enterprise-grade Retrieval-Augmented Generation (RAG) systems using Amazon Bedrock Agents and SingleStore. Learn how to leverage the combined power of Amazon Bedrock for intelligent AI agents equipped with custom tools, and SingleStore for high-performance data processing to create scalable, robust RAG applications. This session will cover practical strategies, real-world examples, and a live demonstration on how to build and deploy a RAG pipeline that can handle data complexity and speed required for enterprise solutions.

You’ll learn:

• The fundamentals of Retrieval-Augmented Generation (RAG) and its enterprise applications.
• How to integrate Amazon Bedrock Agents with SingleStore to build scalable RAG systems.
• How to use LangChain and Amazon Bedrock Embeddings for effective data retrieval and augmentation.
• A live demonstration of building an enterprise-grade RAG pipeline from scratch, including setting up agents, developing tools, and deploying the system.

This hands-on workshop is for developers and AI professionals, featuring state-of-the-art technology, case studies, code-share, and live demos. Recording and GitHub material will be available to registrants who cannot attend the free 60-min session.

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