Amazon Textract vs Comprehend for Document Processing

Textract and Comprehend are both AWS AI services used in document processing, but they solve different problems. Textract extracts text and structure from documents. Comprehend analyzes text to extract meaning. Most document processing pipelines need both, used sequentially.

Overview

What Textract Does

Textract is an OCR and document understanding service. It extracts text from scanned documents, photos of documents, and PDFs. Beyond raw text extraction, Textract understands document structure:

• DetectDocumentText extracts raw text with word and line-level bounding boxes
• AnalyzeDocument extracts forms (key-value pairs) and tables with cell-level structure
• AnalyzeExpense specializes in invoices and receipts with pre-trained field extraction
• AnalyzeID extracts structured data from identity documents
• AnalyzeLending handles mortgage document packets

Textract’s Queries feature lets you ask natural language questions about a document (“What is the patient name?”) and get targeted extraction results.

What Comprehend Does

Comprehend is a natural language processing (NLP) service. It takes text as input (not images) and extracts meaning:

• Entity Recognition identifies people, organizations, dates, quantities, and other entities
• Sentiment Analysis classifies text as positive, negative, neutral, or mixed
• Key Phrase Extraction identifies significant phrases
• Language Detection identifies the document language
• Topic Modeling groups documents by discovered topics
• PII Detection identifies and redacts personally identifiable information

Comprehend also supports custom models. Custom Entity Recognition lets you train models to extract domain-specific entities. Custom Classification trains document classifiers on your labeled data.

How They Work Together

The standard document processing pipeline uses Textract first, then Comprehend:

1. Textract extracts text and structure from scanned documents
2. Comprehend analyzes the extracted text for entities, classification, or PII detection

For example, processing insurance claims: Textract extracts text from scanned claim forms, identifies form fields and table data. Comprehend then classifies the claim type, extracts named entities (claimant, dates, amounts), and detects PII for redaction.

When to Use Textract Alone

Use Textract alone when your goal is structured data extraction from documents and you do not need NLP analysis. Digitizing paper forms, extracting tables from PDFs, processing invoices, and reading identity documents are all Textract-only workflows. Textract’s Queries feature and specialized analyzers (Expense, ID, Lending) handle many extraction tasks without needing Comprehend.

When to Use Comprehend Alone

Use Comprehend alone when your text is already digital and you need NLP analysis. Analyzing customer reviews, classifying support tickets, detecting PII in text databases, and topic modeling document collections are Comprehend-only workflows. If your input is already text (not scanned documents or images), Textract is unnecessary.

When to Use Both

Use both when you have scanned or image-based documents and need to understand their content beyond structure. Medical record processing, legal document analysis, and compliance document review typically require Textract for extraction and Comprehend for entity recognition, classification, or PII detection.

Practical Recommendation

Think of Textract as the “eyes” (reading documents) and Comprehend as the “brain” (understanding text). If your documents are digital text, skip Textract. If you only need to extract structured fields, Textract alone may suffice. For end-to-end document intelligence that extracts, classifies, and understands document content, combine both services in a Step Functions workflow with S3 for document storage.