Document Intelligence — Canonical Workflow

What this reference supports

Document intelligence turns PDFs, scans, and forms into structured data by chaining OCR, layout parsing, multimodal understanding, and schema-validated extraction, a pattern often paired with enterprise search and data-analysis workflows downstream, and increasingly relied on to remove manual data entry from back-office processes.

Use this page to check which multimodal models handle your document types and languages, which managed-container or self-hosted extraction architecture fits your volume and latency needs, and what evidence exists for accuracy on layouts, handwriting, and scan quality similar to yours, including scanned or photographed documents rather than clean digital PDFs, and how confidence scoring is surfaced downstream.

Extraction accuracy depends heavily on document quality, layout complexity, language, and schema design — this is provisional decision support, not a guarantee of accuracy on your specific document set. Validate against a representative sample, including edge-case scans and multi-page forms, and keep a human-review checkpoint for low-confidence extractions before they reach downstream systems.