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Using large language models with your company’s internal data can be challenging. To create a trustworthy and stable solution, you need a system that is accurate, efficient, and secure. Building a prototype is one thing, but deploying a system that you can scale and maintain at an enterprise level requires a clear strategy. This book shows you how to build production-ready RAG systems that meet business demands. Build an enterprise-level RAG system that scales to meet demand. Learn to use RAG with SQL databases and internal documentation. Create fast and accurate searches for your applications. Discover how to prevent AI hallucinations and inaccurate completions. Monitor, scale, and maintain RAG systems in a cost-effective way. Enterprise RAG shows how to build reliable RAG systems for real use in organisations. The book draws on practical experience from real projects. It explains simple ways to improve search, refine questions, and get better results from your system. After reading this book, you will know how to sidestep common problems and handle challenges like choosing the right LLM. You will be able to build data workflows that maximise accuracy and address cost and performance issues. This book is for software developers who are proficient in Python and want to build reliable RAG solutions.
