AWS document intelligence service that extracts text, tables, forms, and handwriting from scanned documents using machine learning — with specialized APIs for invoices, IDs, and lending documents.
AWS service that reads text, tables, forms, and handwriting from scanned documents automatically using machine learning.
Amazon Textract is AWS's managed document intelligence service for extracting structured data from scanned documents, PDFs, and images. It goes beyond basic OCR by using machine learning to understand document structure — identifying tables with preserved cell relationships, extracting form key-value pairs without templates, and reading handwritten text alongside printed content.
Textract offers multiple extraction APIs for different use cases. DetectDocumentText handles high-speed OCR at $0.0015/page, suitable for bulk text extraction from research reports or digitization projects. AnalyzeDocument adds structural understanding — extracting tables ($0.015/page), forms with key-value pairs ($0.05/page), and responding to custom queries about specific data points. Specialized APIs handle invoices and receipts (AnalyzeExpense), identity documents (AnalyzeID), and mortgage documents (AnalyzeLending) with domain-specific intelligence.
The service processes documents synchronously for single pages or asynchronously via S3 for multi-page documents up to 3,000 pages. Async processing runs as background jobs with SNS notifications on completion, integrating naturally into AWS workflows with Lambda triggers, DynamoDB storage, and Kendra search.
Textract's handwriting recognition is a differentiator, accurately extracting handwritten notes, filled forms, and signatures that trip up many competing OCR services. This makes it valuable for healthcare intake forms, legal documents, and government workflows where handwritten content is common.
Pricing uses a pay-per-page model with significant volume discounts after 1 million pages monthly. Basic OCR drops from $0.0015 to $0.0006/page at scale. A free tier offers 1,000 pages/month for basic OCR and 100 pages/month for advanced features during the first 3 months for new AWS customers.
The main limitations are the lack of custom model training (you're limited to prebuilt models), complex JSON output that requires preprocessing for LLM and RAG applications, and table extraction accuracy that trails Azure Document Intelligence on highly complex layouts. The synchronous API is limited to single pages — multi-page processing requires S3 storage and the async workflow.
Textract is strongest for AWS-native organizations already invested in the ecosystem, high-volume OCR operations where per-page pricing matters, and document processing workflows that benefit from tight integration with S3, Lambda, and other AWS services.
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Amazon Textract provides reliable OCR and document extraction backed by AWS's infrastructure and scale. The Queries feature lets you ask natural language questions to extract specific information from documents. Integration with the broader AWS ecosystem (S3, Lambda, Step Functions) makes it straightforward to build document processing pipelines. Accuracy is good for printed text but can struggle with handwriting and complex layouts. Pricing is per-page and competitive with Azure Document Intelligence.
Preserves cell relationships, merged cells, and complex table structures from documents, outputting structured data rather than raw text.
Use Case:
Extracting financial data from quarterly reports where tables contain merged headers, subtotals, and multi-column layouts.
Automatically identifies and extracts key-value pairs from forms without requiring templates or pre-defined field locations.
Use Case:
Processing thousands of insurance claim forms that vary in layout but contain similar fields like policy number, date, and amount.
Accurately reads handwritten text alongside printed content, including filled-in form fields and handwritten notes.
Use Case:
Digitizing patient intake forms in healthcare where patients handwrite their medical history and contact information.
Ask specific questions about a document and Textract extracts the targeted information, useful for pulling specific data points from varied document formats.
Use Case:
Extracting 'total amount due' and 'due date' from invoices that have different layouts across vendors.
Free
month
Pay-per-page, no minimum
Features stack — each adds to per-page cost
Domain-specific extraction models
Ready to get started with Amazon Textract?
View Pricing Options →AWS-native document processing pipelines leveraging S3, Lambda, and SNS
High-volume OCR operations where per-page pricing at scale matters
Invoice and expense processing with the specialized AnalyzeExpense API
Healthcare and legal document digitization requiring handwriting recognition
Form processing and data extraction from business documents at scale
We believe in transparent reviews. Here's what Amazon Textract doesn't handle well:
Textract delivers competitive accuracy (95-98%) for standard documents and excels at handwriting recognition. Azure Document Intelligence often outperforms on complex table layouts and offers custom model training that Textract lacks. Textract wins on per-page pricing at high volumes.
No. Textract only offers prebuilt models for general documents, forms, tables, invoices, IDs, and lending documents. For custom extraction, consider Azure Document Intelligence or Google Document AI which support custom model training.
Up to 3,000 pages using the asynchronous API with S3 storage. Individual pages can be up to 10MB. The synchronous API is limited to single pages.
Textract requires significant post-processing for RAG. The JSON output includes bounding boxes and hierarchical structures that need conversion to clean text or markdown before feeding to vector databases or LLMs. Build preprocessing pipelines for clean output.
Volume discounts kick in after 1 million pages/month. Basic OCR drops from $0.0015 to $0.0006/page. Table extraction drops from $0.015 to $0.01/page. Form extraction drops from $0.05 to $0.04/page. At 2M pages/month, basic OCR costs about $2,100.
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