Building an Agentic RAG Pipeline

Description

Agentic RAG (Retrieval-Augmented Generation) represents the next evolution of intelligent information retrieval. While traditional RAG combines external data with large language models, Agentic RAG empowers AI agents to autonomously refine queries, manage retrieval, and enhance the accuracy of generated responses. In this session, Francesco Esposito breaks down: - The key differences between standard RAG and Agentic RAG - How intelligent agents improve accuracy, scalability, and adaptability - Practical steps for implementing Agentic RAG pipelines in real-world applications Website → https://mlconference.ai/?loc=all Blog → https://mlconference.ai/blog/ FAQ → https://mlconference.ai/faq/ Newsletter → https://mlconference.ai/newsletter/ Bluesky → https://bsky.app/profile/mlcon.bsky.social Linkedin → https://www.linkedin.com/company/machine-learning-conference/