Extend vs. AWS Textract: Accuracy, Features, Pricing, and Tradeoffs

The verdict: Choose AWS Textract when you need low-cost text detection or AWS-native forms, tables, queries, and signature detection, and your team is ready to build the rest of the document pipeline. Choose Extend when the output must arrive as reviewed, schema-defined data and errors in complex forms, tables, handwriting, or mixed document packets carry downstream cost.

AWS Textract is a managed document analysis service. It returns text, layout, key-value pairs, tables, selection elements, query answers, signatures, and preset outputs for expenses, US identity documents, and mortgage packets. Those are useful primitives. For general business documents, your application still maps the returned block graph into its own data model, reconstructs relationships that span pages, sets review thresholds, and measures quality.

Extend is a document processing platform. It parses documents into markdown and spatial blocks, extracts values into a user-defined JSON schema, splits and classifies mixed files, fills PDF forms, runs multi-step workflows, and attaches confidence, citations, review, and evaluation to the output. The document pipeline is the product, not an integration project around the product.

The accuracy gap is measurable on complex production documents. On RealDoc-Bench, an open-sourced benchmark published by Extend with a public dataset and an arXiv paper, Extend Parse 2.0 scored 95.7% field-level QA accuracy. AWS Textract scored 70.5%.

Extend vs. AWS Textract at a glance

The table below uses Extend's current documentation, Amazon Textract's developer guide, and both vendors' pricing pages. It separates documented capability from the engineering required to turn that capability into production output.

Decision area		AWS Textract
Core product	Document processing platform for parsing, extraction, splitting, classification, editing, workflows, evaluation, and review	Managed AWS service for text detection and document analysis
Best fit	Accuracy-critical document pipelines and agents that need target-schema output and quality operations	AWS-native applications that need text, forms, tables, queries, signatures, or specialized AWS document APIs
Input types	35+ file types, including PDFs, images, spreadsheets, presentations, and scanned files	JPEG, PNG, PDF, and TIFF; synchronous PDF and TIFF processing is limited to one page, while asynchronous jobs support up to 3,000 pages
Parsing output	Layout-aware markdown plus blocks for text, tables, figures, and key-value pairs with spatial metadata	A graph of Block objects for pages, lines, words, layout regions, tables, cells, key-value pairs, queries, signatures, and selection elements
Schema-defined extraction	User-defined JSON Schema with nested objects, arrays, enums, dates, currency, signatures, field instructions, citations, and confidence	Forms return key-value pairs; Queries and Custom Queries target requested answers; preset business schemas cover expenses, US IDs, and mortgage packets
Complex layouts	Parse 2.0 detects 11 semantic block types: text, heading, section heading, figure, table, key-value, page number, barcode, formula, header, and footer. Every block includes its position in the document, with reading order and bounding boxes for downstream processing.	Layout returns headings, headers, footers, lists, tables, figures, key-value regions, and text in implied reading order
Tables	Advanced table parsing supports structured table output, cell blocks, HTML output, and header continuation across pages	Tables mode returns cells, merged cells, titles, footers, headers, and selection elements; AWS documents inconsistent results on merged or irregular tables
Checkboxes and selection elements	Parse 2.0 is tuned for dense checkbox regions; extracted fields can preserve state, label association, citations, and confidence	Detects checkboxes, radio buttons, circled text, underlined text, and crossed-out text with state and geometry inside forms and tables
Handwriting	Agentic OCR can review and correct low-confidence OCR and difficult handwriting	Supports handwriting in English; AWS recommends confidence thresholds and human scrutiny for sensitive workflows
Languages	Parse is documented for multilingual documents and non-Latin text; test the exact language and layout mix in a bakeoff	Text detection supports English, French, German, Italian, Portuguese, and Spanish; handwriting and Queries are English-only
Figures and charts	Figures are first-class blocks; advanced chart extraction can convert chart content into structured tables	Layout can identify figure regions, but chart values and figure structure require another model or custom processing
Signatures	Detects signature blocks and supports a schema type with is_signed, printed name, date, and signer role	Detects handwritten and electronic signatures and initials, returning location and confidence
Citations and traceability	Each extracted field can carry confidence and a citation back to the source region	Blocks and query answers carry geometry and confidence; mapping those objects to business fields is application code
Mixed document packets	General splitting and classification are first-class processors and workflow steps	Analyze Lending classifies and splits mortgage packets; other mixed-document use cases require custom routing or other AWS services
Human-in-the-loop review and QA	Review Agent flags likely extraction issues, and Studio gives the customer's team an interface to inspect and correct output. Evaluation sets score changes against validated outputs.	Confidence scores are included; Amazon A2I can route low-confidence form key-value results into a configurable reviewer workflow; evaluation is customer-owned.
Document editing	/edit detects and fills PDF form fields from instructions or a schema and returns a completed PDF	Read-only; Textract has no API for writing values back into a document
Workflow operations	Versioned processors and workflows combine parse, extract, classify, split, validation, and review	Orchestration is assembled with S3, Lambda, Step Functions, EventBridge, SNS, SQS, A2I, and application code
Deployment and controls	Cloud for all tiers; self-hosted deployment, custom models, SSO/SAML, and advanced RBAC on Enterprise	AWS-managed regional service with IAM, AWS PrivateLink VPC endpoints, CloudTrail, and AWS compliance programs
Enterprise readiness	Self-hosted deployment, custom MSA/DPA/SLA, SSO/SAML, advanced RBAC, multiple workspaces, custom models, custom rate limits, dedicated support, deployed engineering, and a HIPAA BAA are available on Enterprise. Versioned workflows, evaluation sets, Review Agent, and a configurable human-in-the-loop review step provide the document-specific quality controls required for production.	Strong AWS procurement, identity, networking, audit, and compliance foundations. Textract remains a document analysis service, so document-specific evaluation, workflow versioning, review operations, target-schema mapping, and post-processing remain customer-owned or require additional AWS services.
Pricing and free tier	Full product access starts with 10,000 free credits and no listed three-month cutoff. Pay As You Go is $0.0125 per additional credit. Scale is $500 per month with 50,000 credits, $0.01 additional credits, volume discounts, higher rate limits, Slack support, and a HIPAA BAA add-on.	The free tier is limited to new AWS customers for three months. It includes 1,000 text pages per month, but most forms, tables, layout, queries, expense, and ID allowances are 100 pages per month; Custom Queries has no free tier. Paid pricing varies by API, feature, region, and volume.

RealDoc-Bench: accuracy on production documents

RealDoc-Bench measures whether parsed output preserves enough structure for an answering model to return verified values. The corpus contains real-world documents seen in production and 1,356 field-level questions across financial services, real estate, logistics, and healthcare. Scores are calculated at the individual expected-value level.

These are benchmark results on this corpus, not universal field-accuracy claims. Extend published and open-sourced the benchmark. The dataset, methodology, parsed outputs, and paper are public so teams can inspect the test and re-score it.

The failure pattern matters more than the aggregate. Textract usually finds text on simple pages. The gap opens when an answer depends on structure: binding a checkbox to the right label, keeping a handwritten value with its field, reconstructing a form that looks like a table, reading a dense compliance grid, or preserving hierarchy inside a figure. In these cases, text presence is not enough. The output must preserve the relationship that gives the text meaning.

How the implementation responsibility differs

Both products expose APIs. They hand your engineering team different amounts of unfinished work.

A typical AWS Textract production path

1. Choose DetectDocumentText, AnalyzeDocument, or a specialized API.
2. Select feature types such as Forms, Tables, Queries, Layout, and Signatures.
3. Use synchronous calls for eligible single-page files or build an S3-backed asynchronous job flow for multi-page documents.
4. Walk the returned Block graph and its child, value, and answer relationships.
5. Map blocks, geometry, and confidence into your application's target schema.
6. Reconstruct cross-page tables, repeated fields, and document-specific relationships.
7. Set confidence thresholds and connect low-confidence form fields to Amazon A2I or a custom review UI.
8. Build a labeled test set, scoring logic, regression checks, and release gates.
9. Add classification, splitting, downstream validation, and orchestration with other AWS services where needed.

Textract removes OCR model development. It does not remove document-pipeline development.

A typical Extend production path

1. Choose Parse for document-native output or define the business object as an Extract JSON Schema.
2. Configure the accuracy, latency, table, chart, signature, handwriting, and chunking settings for the corpus.
3. Add Split and Classify when files contain multiple document types.
4. Run the processor through the API, an SDK, or a versioned workflow.
5. Consume schema-shaped values with per-field confidence and citations.
6. Route Review Agent issues into the platform review interface so your team can inspect and correct flagged output.
7. Score representative documents in an evaluation set before shipping a processor or workflow change.

Extend removes more of the post-processing and QA layer. Your team still defines the schema, validates the corpus, and decides what level of confidence is acceptable.

Tables, checkboxes, handwriting, and charts

Tables

AWS Textract has real table support. It returns cells, row and column indexes, merged cells, headers, titles, footers, and geometry. AWS also warns that merged cells and irregular row or column structures can produce inconsistent results. Teams that need a final business object must still normalize those blocks, join tables across pages, and handle layout drift.

Extend's table pipeline can return markdown or HTML, include cell-level blocks, continue headers across pages, and feed the normalized table directly into schema extraction. The value is not a claim that Textract cannot see tables. The value is less reconstruction work and higher measured downstream answer accuracy on complex tables.

Checkboxes and forms

AWS Textract detects selection elements and can attach them to a form key-value pair or table cell. The harder problem is preserving the correct association in dense forms, multi-column scans, and nested tables where adjacent labels, columns, and repeated sections compete for the same mark.

Extend's parser treats forms and key-value regions as first-class layout types. Extract then maps the selected state into the requested schema with a source citation and confidence. RealDoc-Bench includes dense medical, mortgage, and logistics forms specifically because association errors can look plausible while changing the answer.

Handwriting and languages

AWS Textract supports printed text in six languages and handwriting in English. Queries are also English-only. Extend supports multilingual files, non-Latin text, and difficult handwriting, with agentic OCR available for low-confidence corrections. Language support is still corpus-dependent. Test the exact scripts, scan quality, handwriting styles, and mixed-language pages you expect in production.

Figures and charts

Textract Layout can label a figure region and return the text around it. It does not turn a chart into a table of data points. That requires a separate vision model or custom interpretation step. Extend can preserve figures as blocks and optionally convert chart content into structured tables, which gives agents a usable representation instead of a figure placeholder.

Pricing: compare equivalent work

Extend offers the more generous free and growth tiers for teams evaluating a complete document platform. Extend's pricing page includes 10,000 free credits with access to Parse, Extract, Classify, Split, Edit, Studio, evals, Composer, Review Agent, agentic OCR, and workflows. The page does not list a three-month cutoff. After the free credits, Pay As You Go costs $0.0125 per credit.

AWS offers the lower raw OCR unit price, but its Textract free tier is narrower and time-limited. It is available to new AWS customers for three months. Detect Document Text includes 1,000 pages per month, while most forms, tables, layout, queries, expense, and ID allowances are 100 pages per month. Custom Queries has no free allowance.

Textract's headline price depends on the feature. In US West (Oregon), AWS's current examples price raw text detection at $0.0015 per page for the first one million pages, tables at $0.015 per page, and forms at $0.05 per page. Calling forms and tables together is additive in AWS's example, for $0.065 per page. Queries, Custom Queries, signatures, expenses, IDs, and lending have separate pricing.

Extend uses credits across the platform. The number of credits per page depends on the processor and configuration, so compare the exact Parse or Extract mode required for the workload. Scale lowers the additional-credit rate from $0.0125 to $0.01 and includes 50,000 credits each month.

For clean text extraction, Textract is much cheaper. For accuracy-critical extraction, compare equivalent work: the selected Textract features, AWS orchestration, block-to-schema code, review infrastructure, and error-driven rework against the Extend processor and review path that would replace them.

When to choose AWS Textract

Choose AWS Textract when:

• You need inexpensive OCR for clean PDFs or images.
• Forms, tables, queries, signatures, AnalyzeExpense, AnalyzeID, or Analyze Lending match the document set.
• Your application already uses S3, IAM, Lambda, Step Functions, and AWS monitoring.
• Your team wants block-level primitives and is prepared to own schema mapping, evaluation, and review operations.
• AWS procurement, regional availability, PrivateLink, or an existing enterprise agreement decides the architecture.
• Speed and unit cost matter more than maximum accuracy on complex layouts.

When to choose Extend

Choose Extend when:

• The output must match your schema across changing document types.
• Complex tables, dense forms, handwriting, checkboxes, charts, and mixed packets are common rather than exceptional.
• You need citations and confidence attached to business fields, not only source blocks.
• You need parsing, extraction, classification, splitting, form filling, and workflows in one platform.
• You want a free tier that includes the full platform or a packaged growth tier with credits, lower overage pricing, volume discounts, and direct support.
• You want an evaluation set, accuracy reports, and a platform review interface that enables your team to inspect and correct flagged output before production traffic arrives.
• Errors affect underwriting, claims, compliance, payments, patient records, logistics, or other systems of record.
• A self-hosted deployment, custom model, SSO/SAML, or advanced RBAC is required.

What to test before choosing

Do not choose a document platform from a feature checklist alone. Run both systems on the documents most likely to break them.

1. Select 25 to 100 representative documents, including the worst scans and longest tables.
2. Define the exact target schema and ground-truth values before testing either vendor.
3. Include handwriting, unchecked and checked boxes, signatures, repeated labels, merged cells, multi-page tables, and mixed document packets.
4. Score field completeness and correctness. Count timeouts and failed runs as failures.
5. Measure latency, per-page processing cost, and human-in-the-loop review volume at the same accuracy threshold.
6. Make one schema or document-template change and measure the engineering work required to ship it safely.
7. Inspect the source trace for every wrong answer. Determine whether the failure came from OCR, layout, association, schema mapping, or review routing.

The winning system is the one that produces the required business object at the required accuracy with the lowest total operating cost.

Extend vs. AWS Textract: frequently asked questions

What is the best AWS Textract alternative for complex document extraction?

Extend is the strongest AWS Textract alternative when complex-document accuracy and production QA are the requirements. Extend Parse 2.0 scored 95.7% field-level QA accuracy on the open-sourced RealDoc-Bench compared with 70.5% for Textract, and Extend includes schema extraction, splitting, classification, review, evals, workflows, and form editing in the same platform.

Does AWS Textract support checkboxes?

Yes. Textract returns checkboxes and other selection elements with selected or unselected state, geometry, and relationships to forms or table cells. The comparison is not checkbox detection versus no checkbox detection. It is whether the final pipeline preserves the right label-state relationship on dense forms and delivers that value in the target schema.

Does AWS Textract support handwriting and multiple languages?

Textract supports handwriting in English. Printed text detection supports English, French, German, Italian, Portuguese, and Spanish. Queries are English-only. Extend supports multilingual and non-Latin documents and can use agentic OCR for difficult handwriting, but teams should test their exact languages and scan conditions.

Is Extend more accurate than AWS Textract on complex production documents?

Yes. On the Extend-published, open-sourced RealDoc-Bench, Extend Parse 2.0 scored 95.7% field-level QA accuracy against 70.5% for AWS Textract. Extend also led every measured industry slice by 20.7 to 42.2 percentage points and scored 0.847 adjusted F1 on layout understanding compared with 0.709 for Textract.

Is AWS Textract cheaper than Extend?

For raw text detection, yes: AWS lists $0.0015 per page for the first one million pages in US West (Oregon). Extend has the more generous access tiers. Its free tier includes 10,000 credits and the full platform with no listed three-month cutoff, while Textract's free tier lasts three months for new AWS customers and limits most structured features to 100 pages per month. Structured AWS features also cost more than raw OCR, including $0.015 per page for tables and $0.05 per page for forms. Compare total workflow cost, including reconstruction, review, and rework.

Can Extend run in an AWS architecture?

Yes. Extend is accessible through REST and SDKs for Python, TypeScript, Java, and Go, with asynchronous runs and webhooks for production workflows. Enterprise customers can also use self-hosted deployment. Start with 10,000 free credits and test both systems on the same corpus.

Does Extend replace every AWS service around Textract?

No. Extend replaces the document-processing and quality layer, not AWS infrastructure. Teams can keep S3, queues, databases, observability, and application services while using Extend for parse, extract, classify, split, edit, review, and evaluation.