Amazon Textract Tutorial: Get Started in 5 Minutes [2026]

What it does:

Preserves table structure with cell relationships, headers, and merged cells, returning structured JSON that maintains row and column relationships. Output can be directly converted to CSV or inserted into databases without manual reconstruction. Priced at $0.015/page, dropping to $0.01/page above 1 million pages monthly.

Use case:

What it does:

Automatically identifies form fields and extracts key-value pairs without requiring predefined templates or manual configuration. Handles checkboxes, radio buttons, and text fields across various form layouts, adapting when forms change. Priced at $0.05/page — the most expensive Textract feature, reflecting its complexity.

Use case:

What it does:

Advanced ML models trained specifically for handwritten text extraction, handling cursive writing, mixed handwritten/printed documents, and signatures. Reddit users report 85-90% accuracy on handwritten content — meaningfully better than Azure and Google for cursive. Included in standard pricing with no premium charge.

Use case:

What it does:

Ask natural language questions to extract specific information from documents — query 'What is the total amount?' or 'Who is the vendor?' and receive targeted responses with confidence scores. Eliminates the need for custom parsing logic for one-off extractions. Particularly useful for unique document types not covered by specialized APIs.

Use case:

What it does:

Purpose-built APIs for invoices (AnalyzeExpense), identity documents (AnalyzeID), and lending documents (AnalyzeLending) with pre-trained field extraction for domain-specific schemas. AnalyzeLending alone extracts data from W-2s, 1099s, pay stubs, and bank statements without configuration. These APIs reduce custom development by months for industry-specific workflows.

Use case: