4.3. Document Intelligence and Content Understanding
💡 First Principle: Before you can chunk or retrieve, you often must extract structure from messy source files — and that's a different job from retrieval. Document Intelligence and Content Understanding turn PDFs, forms, and multimodal files into structured fields and layout, which then feed the RAG pipeline. Extraction is upstream of retrieval, not a substitute for it.
Why care: the domain is named "information extraction" because grounding starts with getting clean, structured content out of documents. A scanned invoice or a complex form isn't directly chunk-able as raw text; you extract its fields and layout first. Recognizing when a requirement needs extraction (structure from documents) versus retrieval (finding relevant chunks) is the cross-cutting distinction.
⚠️ Common Misconception: Learners conflate "extract data from this document" with "search across documents." Extraction (Document Intelligence / Content Understanding) pulls structured fields and layout from a given file; retrieval (AI Search) finds relevant passages across a corpus. They're sequential stages, not alternatives.
