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Multimodal
Document AI
Definition
Document AI processes and extracts structured information from documents like PDFs, invoices, and forms, combining OCR with language understanding to automate document workflows.
Why It Matters
Organizations process millions of documents - invoices, contracts, forms, reports. Manual data entry is slow, expensive, and error-prone. Document AI automates extraction of structured data from unstructured documents, reducing processing time from hours to seconds.
Capabilities
Information Extraction:
- Key-value pairs (invoice number, date, amount)
- Tables and line items
- Addresses and contact information
- Signatures and handwriting
Document Understanding:
- Classification (what type of document?)
- Layout analysis (sections, headers, paragraphs)
- Semantic understanding (what does this clause mean?)
Implementation Options
- Cloud Services: AWS Textract, Google Document AI, Azure Form Recognizer
- Vision-Language Models: GPT-4o, Claude for flexible extraction
- Specialized Models: LayoutLM, Donut for document-specific tasks
- Open Source: PaddleOCR, DocTR for self-hosted solutions
When to Use
Document AI is valuable when: you process high volumes of similar documents, you need structured data from unstructured sources, manual data entry is a bottleneck, or you need to search across document archives.