azure-ai-document-intelligence-ts

To extract structured data from invoices using TypeScript, you can use Azure Document Intelligence with the prebuilt-invoice model to parse vendor names, line items, and totals from URLs or base64 inputs.

Yes, Azure Document Intelligence supports batch processing and table extraction. You can submit multiple documents to a result container and use the prebuilt-layout model to parse tables and text asynchronously.

Yes, you need an active Azure Document Intelligence endpoint and credentials to extract text from PDF documents. The service requires authentication to process URLs or base64 file inputs and return structured outputs.

The best way to handle long-running OCR operations in TypeScript is using long-running pollers. Azure Document Intelligence uses asynchronous operations with explicit error checking via isUnexpected to manage extraction status safely.

Yes, Azure Document Intelligence works with custom forms and ID documents. You can build custom document models and classifiers for specialized types, or use prebuilt models to extract domain fields from various forms reliably.

Document extraction fails with local files if they are not properly encoded as base64. Azure Document Intelligence requires inputs as either accessible URLs or base64 encoded strings, and uses isUnexpected checks to catch validation errors.