Building Production LLM Systems: The Practitioner's Guide to Open-Source AI: Design, Deploy, and Fine-Tune LLaMA, Mistral, and Self-Hosted Language Models for Scalable, Privacy-Preserving Enterprise

Moon, Cedar

ISBN 13: 9798277266137

Published by Independently published, 2025

About this Item

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Seller Inventory # I-9798277266137

Bibliographic Details

• Title: Building Production LLM Systems: The Practitioner's Guide to Open-Source AI: Design, Deploy, and Fine-Tune LLaMA, Mistral, and Self-Hosted Language Models for Scalable, Privacy-Preserving Enterprise
• Publisher: Independently published
• Publication Date: 2025
• Language: English
• ISBN 13: 9798277266137
• Binding: Soft cover
• Condition: New

About this title

Synopsis

Building Production LLM Systems is the comprehensive engineering guide for deploying open-source language models at enterprise scale. Written by Cedar Moon, a veteran who has shipped multiple million-dollar LLM systems, this practitioner's handbook covers everything from selecting the right model family (LLaMA, Mistral, Mixtral) to building production-ready infrastructure that rivals proprietary APIs.

Across 15 detailed chapters, you'll master quantization techniques that run 70B models on consumer GPUs, inference optimization strategies delivering 3-8× higher throughput, fine-tuning pipelines for 405B parameters on a single card, and RAG systems ready for regulatory scrutiny. The book includes production-tested code, real infrastructure cost models, security hardening for regulated industries, and MLOps patterns for continuous improvement.

This isn't theory—it's battle-tested wisdom from real deployments across finance, healthcare, and defense. Whether you're running your first 7B model or orchestrating a thousand-GPU cluster, you'll gain the complete playbook to build LLM systems that are faster, cheaper, and more secure than any API—while maintaining full ownership of your AI stack.

Stop renting intelligence. Start owning it.