# Amazon Textract

Cloud service · AWS. Updated 2026-10-29. Page: https://blowstack.com/tools/cloud-services-hub/amazon-textract

> Amazon Textract is a fully managed machine learning service that automatically extracts text, handwriting, and data from scanned documents.

Practice exams covering Amazon Textract: [AIB-C01 (beta) AWS Certified AI Business Strategist](https://blowstack.com/practice-exams/aws-certified-ai-business-strategist), [AIF-C01 AWS Certified AI Practitioner](https://blowstack.com/practice-exams/aws-certified-ai-practitioner), [CLF-C02 AWS Certified Cloud Practitioner](https://blowstack.com/practice-exams/aws-certified-cloud-practitioner), [AIP-C01 AWS Certified Generative AI Developer - Professional](https://blowstack.com/practice-exams/aws-certified-generative-ai-developer-professional), [MLA-C02 (beta) AWS Certified Machine Learning Engineer - Associate](https://blowstack.com/practice-exams/aws-certified-machine-learning-engineer-associate).

## 6 key features of Amazon Textract

Amazon Textract offers features such as accurate text extraction from documents and images, form and table recognition, handwriting recognition, easy integration with APIs, locating text with bounding box information, and supports multiple languages, facilitating comprehensive document processing and analysis.

1. **Text Extraction**: Amazon Textract can accurately extract text, forms, and tables from images and documents with varying layouts without manual effort, using machine learning to read and process any type of document.
2. **Form and Table Recognition**: It offers advanced features to identify the structure of forms and tables within documents, enabling users to understand and utilize the extracted information contextually.
3. **Handwriting Recognition**: Textract has the capability to recognize handwritten text from notes, forms, or any other documents, making it easier to digitize and process handwritten documents.
4. **Integrations and APIs**: It provides seamless integration with other AWS services and accessible APIs, allowing for easy incorporation into workflows and enabling automation of document processing tasks.
5. **Bounding Box Information**: Amazon Textract provides bounding box coordinates for each detected text element, which helps in locating text within a document and can be used for document analysis and editing.
6. **Language Support**: Supporting multiple languages, Textract aids in global operations by processing documents in various languages, thus broadening its usability internationally.

## Where Amazon Textract is used

Amazon Textract facilitates automation and digital transformation across various sectors by extracting text and data from documents, enabling streamlined workflows, enhanced decision-making, and improved data accuracy in industries such as finance, healthcare, legal, and education.

1. **Automated Document Processing**: Amazon Textract can be used to automate the processing of various document types, such as forms, invoices, and receipts. This function facilitates the extraction of text, forms, and tables, enabling businesses to streamline their document workflows, increase efficiency, and reduce manual errors.
2. **Mortgage Application Analysis**: In the financial services industry, Textract can dramatically improve the mortgage application process by extracting key data points from application forms and supporting documents. This can accelerate decision-making processes, improve customer satisfaction, and ensure higher accuracy in data handling.
3. **Medical Records Digitization**: Healthcare organizations can use Amazon Textract to digitize patient records, extract clinical information, and integrate it with electronic health record (EHR) systems. This enhances patient care through better data availability and accuracy while ensuring compliance with data privacy regulations.
4. **Legal Document Analysis**: Law firms and legal departments can leverage Textract to analyze large volumes of legal documents, extracting specific clauses, dates, and other pertinent information. This enables faster case analysis, eases compliance checks, and optimizes knowledge management practices within the legal industry.
5. **Educational Content Digitization**: Educational institutions and e-learning platforms can use Amazon Textract to digitize textbooks, research papers, and other educational materials. By extracting text and data from these documents, they can create searchable, accessible content that enhances the learning experience for students.

## How Amazon Textract is priced

Amazon Textract provides a pay-as-you-go model for both the Analyze Document and Detect Document Text APIs, with costs varying by usage and a volume discount model for committed monthly usage.

- **Pay-As-You-Go for Analyze Document API**: Amazon Textract charges for the Analyze Document API on a per-page basis. Charges depend on the features used such as text detection or form/table data extraction.
- **Pay-As-You-Go for Detect Document Text API**: This pricing model also operates on a per-page basis but is tailored for customers only needing to extract plain text from documents. It is generally cheaper than the Analyze Document API.
- **Monthly Volume Discounts**: Per-page pricing has volume tiers based on the number of pages processed per month.
- **Pay-As-You-Go for Analyze Expense API**: Analyze Expense is charged per page; in US West (Oregon), the rate is $0.01 per page for the first million pages per month and $0.008 per page thereafter.
- **Pay-As-You-Go for Analyze ID API**: Analyze ID is charged per page; in US West (Oregon), the rate is $0.025 per page for the first 100,000 pages per month and $0.01 per page thereafter.
- **Pay-As-You-Go for Analyze Lending API**: Analyze Lending charges for pages receiving supported classification and data extraction; in US West (Oregon), the rate is $0.07 per page for the first million such pages per month and $0.055 per page thereafter.
- **Pay-As-You-Go for Custom Queries**: Custom Queries has separate per-page pricing; in US West (Oregon), the rate is $0.025 per page for the first million pages per month and $0.015 per page thereafter.
- **Free Tier**: New AWS customers receive a three-month free tier, including up to 1,000 pages per month with the Detect Document Text API.
- **Custom Pricing for High Volume**: High-volume customers can contact AWS sales to request a custom pricing proposal.

## Services Amazon Textract works with

- **[Amazon S3](https://blowstack.com/tools/cloud-services-hub/amazon-s3)**: Amazon Textract can process documents stored in Amazon S3. You simply provide the S3 bucket and object key where the document is located.
- **[AWS Lambda](https://blowstack.com/tools/cloud-services-hub/aws-lambda)**: AWS Lambda can be used to trigger Amazon Textract processing when a new document is uploaded to an S3 bucket. It can also be employed for post-processing tasks after Textract has completed.
- **[Amazon Comprehend](https://blowstack.com/tools/cloud-services-hub/amazon-comprehend)**: Amazon Textract integrates with Amazon Comprehend for further analysis of the text extracted from documents, such as entity recognition, sentiment analysis, and topic modeling.

## What is Amazon Textract

Amazon Textract is an innovative service powered by machine learning, designed to automatically extract text and data from scanned documents. This advanced technology not only recognizes the content of documents with high precision but also understands its structure, such as tables and forms.

One of Textract's key features is its ability to process a vast array of document formats, including scans of physical documents, PDF files, or images, enabling users to automate document handling processes that were previously manual and time-consuming. Amazon Textract's ability to accurately extract data from documents can significantly improve the efficiency of various business operations. For instance, it can automate data entry tasks, speed up document processing, and enhance the management of records by extracting valuable information from invoices, receipts, financial statements, medical records, and legal contracts, among others. This makes it an invaluable tool across multiple sectors, including finance, healthcare, legal, and more, where large volumes of document processing are a common challenge.

AWS regularly improves Amazon Textract's underlying machine learning models based on customer feedback to improve accuracy.

Moreover, Amazon Textract is designed to recognize not only printed text but also handwritten notes in documents, a feature that significantly expands its applicability and utility in real-world scenarios where hand-filled forms and notes are prevalent. Amazon

Textract seamlessly integrates with other AWS services, providing a comprehensive solution for managing document workflows. Once text and data have been extracted, they can be stored, queried, and analyzed using Amazon's vast data management and analytics tools, enabling organizations to gain deeper insights into their operations and make informed decisions based on the extracted data.

Furthermore, Amazon Textract emphasizes security and compliance, ensuring that data is handled and processed with the highest standards of privacy and safety. This is crucial for businesses dealing with sensitive information, as it allows them to leverage the power of cloud-based machine learning while maintaining compliance with regulatory requirements.

In essence, Amazon Textract represents a significant leap forward in document processing technology. By automating the extraction of text and data with remarkable accuracy and efficiency, it offers businesses of all sizes the opportunity to transform their operations, reduce manual workloads, and unlock valuable insights hidden in their documents, all backed by the robust infrastructure and security of Amazon Web Services.

## Concepts related to Amazon Textract

- [Confidence Scoring](https://blowstack.com/tools/cloud-concepts-hub/confidence-scoring): Confidence scoring assigns a numerical measure of estimated reliability to an AI prediction or response so applications can decide whether to accept, verify, or reject it.
- [Document Chunking](https://blowstack.com/tools/cloud-concepts-hub/document-chunking): Document chunking divides source documents into smaller, context-preserving units for indexing, retrieval, and language-model processing.
- [Labor Productivity](https://blowstack.com/tools/cloud-concepts-hub/labor-productivity): Labor productivity is the amount of useful output produced per unit of human labor, commonly measured as quality-adjusted output per labor hour.
- [Machine learning](https://blowstack.com/tools/cloud-concepts-hub/machine-learning): Machine learning is a branch of artificial intelligence that uses data to train models to make predictions, recognize patterns, or generate outputs without explicitly programming every decision rule.
- [Metadata Extraction](https://blowstack.com/tools/cloud-concepts-hub/metadata-extraction): Metadata extraction is the process of identifying and capturing structured attributes from documents, their contents, and their source systems.
- [Task Decomposition](https://blowstack.com/tools/cloud-concepts-hub/task-decomposition): Task decomposition is the practice of breaking a larger activity into smaller, clearly defined tasks that can be assigned to people, software, or AI systems.
- [Text Chunking](https://blowstack.com/tools/cloud-concepts-hub/text-chunking): Text chunking divides documents or other text into smaller, meaningful units for embedding, retrieval, and processing within model input limits.
- [Unstructured Data](https://blowstack.com/tools/cloud-concepts-hub/unstructured-data): Unstructured data is information whose meaningful content does not fit a predefined tabular schema, such as free-form text, images, audio, and video.