Question

Your team is building a RAG solution over engineering maintenance manuals stored as PDFs. Each manual mixes narrative paragraphs, exploded-view diagrams with callout numbers, and specification tables. The downstream agent must reason over the text AND correctly associate diagram callout numbers with their referenced part descriptions in the tables. You need to produce a clean, grounded representation that preserves the reading order, table structure, and figure-to-text relationships in a single pass. Which approach best meets these requirements?

Accepted Answer

Use a Content Understanding multimodal document analyzer that performs layout analysis, OCR, and figure understanding to emit structured markdown preserving reading order, tables, and figure captions/callouts.

Answer

Run the Azure AI Vision Read (OCR) API on each page to extract raw text lines, then concatenate the text in top-to-bottom order for chunking.

Answer

Build an Azure AI Search skillset with only the built-in OCR skill and merge skill, indexing the flat extracted text without layout or figure enrichment.

Answer

Use a text-only prompt to a language model asking it to describe each PDF page, relying on the model's general knowledge to reconstruct the tables and diagrams.