Building Data-Driven Applications with LlamaIndex

Building Data-Driven Applications with LlamaIndex is a practical Packt guide for readers who want to move beyond isolated LLM prompts and build applications that can retrieve, organize, and use external data intelligently. The focus is squarely on retrieval-augmented generation (RAG), LlamaIndex, and the design choices that make data-aware AI systems more useful in real projects.

From LLM Basics to Data-Aware Applications

The opening material establishes why LLMs need help with context, freshness, and reliability, then introduces LlamaIndex as the framework that bridges that gap. Rather than treating the subject as abstract theory, the book uses a hands-on path that helps readers understand how data enters an AI workflow and how it is shaped for retrieval and response generation.

What the Book Covers

• the core building blocks of LlamaIndex, including documents, nodes, and indexes
• data ingestion from web pages, databases, and other sources
• metadata extraction and privacy-aware processing
• indexing, retrieval, response synthesis, and query engines
• workflows and basic agent architectures for more advanced application design

Why It Stands Out

This is not a conceptual survey of generative AI. It is a project-driven guide that moves through the practical mechanics of building working systems, including ingestion pipelines, retrieval strategies, and application structure. The result is especially useful for readers who want a clearer mental model of how RAG systems are assembled and how LlamaIndex fits into that process.

Who Will Find It Useful

The ebook will be most relevant to developers, AI engineers, Python practitioners, and technically minded readers exploring RAG pipelines or building LLM-powered tools with their own data. If you are looking for a structured introduction to LlamaIndex with an emphasis on building rather than merely reading about it, this edition is a strong fit.

Edition Details at a Glance

This listing reflects the Packt ebook edition by Andrei Gheorghiu. The current digital edition is presented as the second edition, with a companion paperback also available separately.