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2.1.3. Document Processing Workloads
Document processing workloads handle structured and semi-structured documents like invoices, receipts, forms, and IDs. These workloads combine multiple AI capabilities—primarily OCR (to read text) with intelligent extraction (to understand what the text means).
Key characteristics:
- Extracts structured information from business documents
- Understands document layout and field relationships
- Can process forms, invoices, receipts, and identity documents
- Goes beyond simple OCR to understand document semantics
- Returns structured data (key-value pairs, tables) not just raw text
How document processing differs from simple OCR:
| Capability | OCR | Document Processing |
|---|---|---|
| Output | Raw text | Structured fields (invoice_number, total, vendor) |
| Understanding | Just reads characters | Understands document type and field meanings |
| Tables | May struggle | Extracts table data with headers |
| Use case | "What text is here?" | "What's the total on this invoice?" |
Common scenarios:
- Invoice processing: Extract vendor, amounts, line items, dates
- Receipt scanning: Capture merchant, items, totals for expense reports
- Form data extraction: Pull field values from filled forms
- ID verification: Extract name, DOB, document number from identity documents
- Contract analysis: Extract parties, dates, key terms from legal documents
Azure service: Azure AI Document Intelligence (formerly Form Recognizer) handles document processing workloads with pre-built models for common document types and custom model training for specific forms.
⚠️ Exam Tip: If a question mentions extracting STRUCTURED DATA from documents (invoices, forms, receipts), think Document Processing. If it just asks about reading text from any image, think OCR.
Written byAlvin Varughese
Founder•15 professional certifications