Lido offers the best document extraction API for teams that want both a developer-friendly REST API and a no-code interface for non-technical users. For pure API infrastructure, Google Document AI and AWS Textract provide the deepest cloud-native capabilities at competitive per-page pricing.
Document extraction APIs turn unstructured documents—PDFs, images, scans—into structured data that software can process. The market in 2026 ranges from cloud provider APIs (Google, AWS, Azure) to specialized extraction platforms to new LLM-powered approaches. Choosing the right API depends on your document types, volume, existing cloud infrastructure, and how much you want to build versus buy.
Here’s how the leading document extraction APIs compare on accuracy, developer experience, pricing, and document type coverage.
Best for: Teams wanting both a REST API for developers and a no-code interface for business users.
Lido’s API accepts any document type—invoices, receipts, bank statements, contracts, forms—and returns structured JSON without requiring document-specific models or training. You define extraction fields in plain English, and the API handles layout understanding, OCR, and data structuring. The same extraction engine powers a no-code web interface, so business users can process documents without API integration. Returns data as JSON, CSV, or direct spreadsheet output. $29/month starting.
Where it's limited: Lido’s API is newer and has a smaller developer ecosystem compared to AWS Textract or Google Document AI. If you need advanced features like custom model training, document classification pipelines, or on-premises deployment, the cloud provider APIs offer deeper infrastructure.
Best for: Teams on Google Cloud wanting pre-trained processors with optional custom model training.
Google Document AI provides pre-trained processors for invoices, receipts, bank statements, W-2s, and other common document types, plus a Custom Document Extractor for training on your specific formats. The API returns structured data with confidence scores and bounding box coordinates. Integrates natively with Google Cloud Storage, BigQuery, and other GCP services. Pricing is per page processed—$0.01–$0.10 depending on processor type.
Where it's limited: Requires Google Cloud Platform account and familiarity. Pre-trained processors work well for supported document types but custom training requires labeled data and time. No user interface—you’re building everything from scratch.
Best for: Teams on AWS needing table and form extraction with serverless processing pipelines.
Textract excels at extracting tables and forms from documents with automatic key-value pair identification. The Analyze Expense API is specifically tuned for receipts and invoices. Deep integration with Lambda, S3, Step Functions, and other AWS services enables fully serverless document processing pipelines. Pay-per-page pricing starts at $0.015 for basic OCR, $0.05 for table/form analysis.
Where it's limited: AWS-specific—integrating Textract into non-AWS environments adds complexity. The API returns raw structure data that requires post-processing to match your schema. No pre-built document-type-specific models (unlike Google Document AI’s processors). Building a complete extraction workflow requires significant development.
Best for: Microsoft ecosystem teams needing document extraction with Power Platform integration.
Azure’s offering (formerly Form Recognizer) provides pre-built models for invoices, receipts, tax forms, and ID documents, plus custom model training. Deep integration with Power Automate, Logic Apps, and the broader Microsoft ecosystem. The Studio interface provides a visual tool for testing and training models. Pricing is competitive with other cloud providers.
Where it's limited: Microsoft ecosystem lock-in. Custom model training requires labeled datasets. Studio interface is useful for prototyping but production requires API integration. Performance can be inconsistent on document types outside the pre-built models.
Best for: Developers wanting fast integration with a clean, well-documented API.
Mindee stands out for developer experience. Clean REST API, comprehensive documentation, client libraries in 7 languages, and a generous free tier (250 pages/month). Pre-built APIs for invoices, receipts, passports, and financial documents. The API is designed to be integrated in hours, not weeks.
Where it's limited: Smaller scale than cloud providers—may not suit extremely high-volume processing. Custom model training is limited compared to Google or Azure. The company is younger and smaller, which some enterprises consider a risk factor.
Best for: Enterprises needing a marketplace of pre-built extraction skills with RPA integration.
ABBYY’s Vantage API provides access to 150+ pre-built document extraction skills covering invoices, purchase orders, contracts, and industry-specific documents. The skill marketplace lets you deploy extraction for new document types without custom training. Deep RPA integration with UiPath, Automation Anywhere, and Blue Prism.
Where it's limited: Enterprise pricing and multi-year commitments. Implementation typically requires professional services. The API complexity reflects the platform’s enterprise positioning—expect a longer integration timeline than developer-focused APIs.
Best for: Teams needing structured data extraction from complex, multi-page documents.
Reducto focuses on turning complex documents into structured data—long contracts, research papers, financial reports with tables, charts, and mixed content. The API handles document understanding beyond simple OCR, identifying sections, relationships, and hierarchies within documents. Useful for documents where structure matters as much as text.
Where it's limited: Newer entrant with a smaller customer base. Best for complex documents rather than high-volume simple extraction (invoices, receipts). Pricing is usage-based and may be higher than cloud provider alternatives for simple use cases.
Best for: Teams wanting LLM-powered document understanding beyond traditional OCR.
Mistral OCR combines traditional OCR with large language model understanding, enabling extraction that considers document context and semantics rather than just character recognition. The approach is particularly strong for documents where field values aren’t in predictable locations—the LLM understands what information is being requested regardless of layout.
Where it's limited: Very new to market with limited production track record. LLM-powered extraction can be slower and more expensive per page than traditional OCR approaches. Accuracy benchmarks are still being established against incumbents.
Best for: Teams processing financial documents who want pre-trained models with a review interface.
Docsumo’s API combines extraction with a built-in validation and review interface. Pre-trained models for invoices, bank statements, and insurance documents. The API returns confidence scores, and low-confidence fields can be routed to human reviewers through Docsumo’s interface. Free up to 100 pages.
Where it's limited: Focused on financial document types—general document extraction is less accurate. API documentation and developer experience don’t match the cloud providers or Mindee. Template setup may be required for optimal accuracy on your specific formats.
Best for: Teams with consistent, recurring documents who want email-triggered extraction.
Parseur’s API integrates with email workflows to automatically extract data from recurring documents—emailed invoices, shipping notifications, booking confirmations. Template-based approach achieves very high accuracy on known formats. Zapier and webhook integrations enable no-code automation.
Where it's limited: Template requirement means every new document format needs manual setup. Not suitable for high-variety document processing. API capabilities are limited compared to the cloud providers—best for specific, repetitive use cases.
Lido is the best all-around document extraction API for teams wanting both developer access and a no-code interface, with support for any document type at $29/month. Google Document AI and AWS Textract are the best pure API infrastructure for teams already on those cloud platforms. Mindee offers the best developer experience for fast integration.
Cloud provider APIs charge per page: AWS Textract $0.015–$0.05/page, Google Document AI $0.01–$0.10/page, Azure similar range. Mindee offers 250 free pages/month, Docsumo 100 free pages. Lido starts at $29/month flat. Enterprise platforms like ABBYY require custom quotes. At high volumes (100,000+ pages/month), cloud provider per-page pricing is typically most economical.
Cloud provider APIs (Google, AWS, Azure) give you maximum flexibility and lowest per-page cost at scale, but require more development to build a complete extraction workflow. Specialized platforms (Lido, Docsumo, Mindee) provide higher-level abstractions, pre-built review interfaces, and faster time-to-production. Choose cloud APIs if you have development resources and need deep customization; choose specialized platforms if you want to extract data this week.
Most modern APIs handle printed text well but struggle with handwriting. Lido and ABBYY Vantage have the strongest handwriting recognition. AWS Textract and Google Document AI handle printed text excellently but have limited handwriting support. If handwritten documents are a significant part of your workflow, test with actual handwritten samples before committing to any API.
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