A water utility must extract dispute evidence from bill packets that include charts and complex layouts, not just plain paragraphs. How should they choose the extraction approach?

A water utility extracting dispute evidence from bill packets that include charts and complex layouts should choose Document Intelligence-style field extraction or Content Understanding based on those chart and layout needs—not Document Intelligence layout OCR with paragraph chunking tuned for chart and complex-layout dispute evidence. Charts, tables, and multi-column bill layouts often carry the usage spikes and fee lines that decide a dispute; richer document understanding recovers that structure. Relying on Document Intelligence layout OCR with paragraph chunking tuned for chart and complex-layout dispute evidence still systematically under-extracts the decisive content because paragraph chunking splits charts and charge tables into text paragraphs instead of recovering field-level values. Indexing bill field content in Azure AI Search with vector embeddings aligned to chart and complex-layout needs still relies on vector recall and won't recover structured chart values and charge-table fields needed for dispute evidence. Processing scanned bills with Document Intelligence read OCR and page-level blocking for chart and complex-layout needs captures surface text but leaves the usage chart and charge table as unstructured blocks, missing the field-level detail needed to verify a usage spike or meter-reading error. Exam caveat: complex municipal bill packets with charts drive Document Intelligence / Content Understanding selection—not Document Intelligence layout OCR with paragraph chunking, Azure AI Search vector embeddings, or Document Intelligence read OCR with page-level blocking. Operational check: classify bill packets by layout complexity; route chart-heavy disputes to the richer extractor; compare extracted usage and fee fields to human review on a holdout set; escalate low-confidence chart reads before customer credit decisions.