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RAG & MCP
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RAG Pipelines — Production Deep Dive

Almost every FDE scenario hides a RAG problem. 80% of RAG failures trace to ingestion and chunking, not the LLM. This section covers every layer in production depth.

End-to-End RAG Pipeline Architecture

End-to-End RAG Architecture

RAG PIPELINE ARCHITECTURE OFFLINE + ONLINE
OFFLINE PIPELINE (BATCH)
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Document Processing

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Document processing for RAG pipelines: PDF parsing, OCR, table extraction, and multi-modal document understanding.

Chunking Strategies

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Text chunking strategies for RAG: fixed-size, semantic, recursive, and document-aware chunking with performance comparisons.

Embedding & Indexing

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Embedding models and vector indexing for RAG: choosing embeddings, HNSW vs IVF, dimensionality, and index optimization.

Embeddings

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Understanding embeddings for AI applications: text, image, and multi-modal embeddings with similarity search and clustering.

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