The preprocessing layer that decides RAG quality before retrieval ever runs. Cleaning, normalization, dedup, quality gates. Grounded in 14-rag-failures and complex-RAG-guide.
Inside the ebook
What you get
Identify the preprocessing choices that drop precision by 10-20 points silently
Clean and normalize text without destroying retrievable structure
Dedup at ingest to avoid recall-killing near-duplicates
Anonymize sensitive entities to cut hallucinations from biased pretraining
Wire quality gates so bad data cannot reach the index