Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
The Claude Code Handbook: Designing scalable RAG pipelines with LangChain, FAISS, Pinecone, and modern vector databases for applied enterprise AI

The Claude Code Handbook: Designing scalable RAG pipelines with LangChain, FAISS, Pinecone, and modern vector databases for applied enterprise AI

Davis, Oren

Paperback

Databases

Currently unavailable to order

ISBN13: 9798267392105
Publisher: Independently Published
Published: Sep 27 2025
Pages: 390
Weight: 1.49
Height: 0.80 Width: 7.00 Depth: 10.00
Language: English
Build reliable, real world RAG systems with Claude, LangChain, and modern vector databases that scale from prototype to production.

Enterprises want accurate, traceable answers, not guesswork. This handbook shows how to design retrieval augmented generation that is fast, auditable, and cost aware, so teams in finance, healthcare, manufacturing, and retail can ship with confidence.

You will move from concepts to hands-on patterns: ingestion, embeddings, vector search, reranking, evaluation, governance, and production operations. Every chapter is engineered for practical use, with defaults that work, pitfalls to avoid, and checklists you can run in CI.

What you will learn

  • How to design end to end RAG pipelines with LangChain and Claude, from loaders and splitters to retrievers, rerankers, and prompts
  • Which vector database to pick and why: FAISS for on premise control, Pinecone for managed scale, Milvus and Qdrant for cloud native or cost sensitive stacks
  • Chunking, hybrid retrieval, contextual compression, and cross-encoder reranking that raise hit rate and precision
  • Evaluation that sticks: faithfulness, groundedness, hit rate, latency budgets, and how to monitor them with dashboards and alerts
  • Security and compliance in production: guardrails, PII redaction, RBAC, audit logging, and data residency routing
  • Scaling patterns that last: GPU indexing, sharding, replication, multi-region and multi-cloud federation
  • Cost control that does not hurt quality: prompt caching, index compression, caching strategies, and SLO driven design
  • Long term maintenance: templates, ADRs, and SLOs that make pipelines repeatable and resilient
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