This second session in our AI Fundamentals series focuses on retrieval-augmented generation (RAG), the essential pattern for connecting large language models (LLMs) to your private data. You will explore the foundational RAG architecture, learn best practices for chunking strategies, and understand how to design robust retrieval workflows to build an application that generates answers based only on your trusted data.
Key takeaways:
- A clear framework for building RAG applications that connect retrieval, chunking, and generation into a usable end-to-end workflow
- The role of chunking and embedding strategies in achieving accurate LLM responses
- How to build RAG applications that answer questions using your enterprise data
Watch this session on-demand to gain the skills you need to build scalable RAG applications. Level up your knowledge on architecture and retrieval workflows to become a more capable AI builder.
Prefer to join live? We run this webinar regularly, with a MongoDB expert there to answer your questions in real time. Save your spot for the next session in your preferred time zone:
