Invoice & document extraction
Extract fields from invoices, orders, expenses, or shipping documents. Apply rules and human review before downstream business use.
Inputs
Scans or images, field definitions, validation rules, and target table format.
Deliverables
Structured tables, source locations, validation results, and a review queue.
Step-by-step workflow
Break the work into verifiable stages, then choose models and supporting tools.
- 01
Define the extraction schema
Specify document types, required fields, amount precision, date formats, and cross-page relationships.
- 02
Recognize and extract
Use vision models or OCR to extract text and tables, retaining page and location references.
- 03
Run validation rules
Programmatically check totals, tax, identifiers, dates, and duplicate documents.
- 04
Review and export
Send uncertain or conflicting fields for human review, then generate files for the business system.
Required model capabilities
Combine models for the actual stages. The directory includes candidates matching one or more of these capabilities.
View matching modelsSupporting tools
Selection & delivery checks
- Test small text, skew, stamps, handwriting, and multi-page tables.
- Recognized numbers need validation and are not automatically accounting facts.
- Follow existing approval processes before writing to business systems.
An example request
Extract structured tables from invoice and order images, validate totals and duplicate IDs in Python, and identify fields needing human review.Find models for this request