Fine-tune VLMs for multipage document-to-JSON with SageMaker AI and SWIFT

Extracting structured data from documents like invoices, receipts, and forms is a persistent business challenge. Variations in format, layout, language, and vendor make standardization difficult, and manual data entry is slow, error-prone, and unscalable. Traditional optical character recognition (OCR) and rule-based systems often fall short in handling this complexity. For instance, a regional bank might need to process thousands of disparate documents—loan applications, tax returns, pay stubs, and IDs—where manual methods create bottlenecks and increase the risk of error. Intelligent document processing (IDP) aims to solve these challenges by using AI to classify documents, extract or derive relevant information, and validate the extracted data to use it in business processes. One of its core goals is to convert unstructured or semi-structured documents into usable, structured formats such as JSON, which then contain specific fields, tables, or other structured target information. The target structure needs to be consistent, so ...