Long gone are the days of manually tuning extraction models for weeks just to process invoices or forms. If you're shipping document processing features, you need more than basic OCR. You need schema versioning so changes don't break production, evaluation tooling to catch accuracy regressions, and workflow orchestration that adapts to different document types. Extend delivers all of this in one API or SDK. Agentic optimization handles schema tuning automatically, multiple processing modes let you balance speed and accuracy per use case, and built-in evaluation frameworks measure quality without custom tooling.

TLDR:

• Document processing APIs convert unstructured files into structured JSON via OCR, VLMs, and LLMs

• Extend delivers 95-99%+ accuracy with agentic optimization that eliminates weeks of manual schema tuning

• Key differentiators: multiple performance modes, schema versioning, and built-in evaluation frameworks

• Production-ready in days with automated quality control, workflow orchestration, and human review UI

• Extend combines agentic OCR, agentic tooling, and enterprise compliance for mission-critical pipelines

What Are Document Processing APIs?

Document processing APIs are software interfaces that convert unstructured documents into structured, machine-readable data. They handle the heavy lifting of extracting information from PDFs, scanned images, forms, invoices, and other document types through a combination of OCR, computer vision, and LLM-based extraction techniques.

Instead of building and maintaining custom extraction models, you call an API endpoint with a document and receive back structured JSON with the parsed data. These APIs handle the complexity of different layouts, image quality issues, handwriting, tables, and multi-page documents.

The output integrates directly into your existing systems, whether that's feeding data into a CRM, triggering workflow automation, or populating a database. This turns documents from static files into actionable data that can drive business logic and decision-making without manual data entry.

The intelligent document processing market reached USD 2.30 billion in 2024 and is projected to grow at a CAGR of 33.1% through 2030. This growth reflects real developer need. In fact, over 70% of IDP solutions in 2025 integrate APIs for connectivity with ERP, CRM, and accounting systems.

How We Ranked Document Processing APIs

When evaluating document processing APIs, we focused on criteria that matter for production deployments, not marketing promises. These are the factors that determine whether an API will actually work for your use case.

First, extraction accuracy on real-world documents. Does the API handle messy layouts, handwriting, tables, and edge cases? Second, API performance including response times and throughput limits. Third, developer experience through SDK quality, documentation, and integration patterns.

We also assessed document format coverage, schema flexibility with versioning support, evaluation and QA tooling for measuring accuracy, and workflow orchestration capabilities for building end-to-end pipelines. Finally, enterprise requirements like SOC2 compliance, HIPAA support, and deployment options.

Best Overall Document Processing API: Extend

Extend is the complete document processing toolkit comprised of the most accurate parsing, extraction, and splitting APIs to ship your hardest use cases in minutes, not months. Extend's suite of models, infrastructure, and tooling is the most powerful custom document solution, without any of the overhead. Agents automate the entire lifecycle of document processing, allowing your engineering teams to process your most complex documents and optimize performance at scale.

Extend gives you five document APIs, built to work alone or together:

• Parse: Convert unstructured documents into structured, LLM-ready markdown. Reliable across any document type.

• Extract: Create a schema and pull exactly the fields you need, across any format of a given document type. Controls that scale to messy real-world data.

• Split: Automatically cut multi-document files into individual subdocuments and classify each page. Perfect for bulk uploads that mix receipts, contracts, invoices, and mail.

• Classify: Route documents based on a prompt and send them to the correct processor. Ideal for triage, routing, and mailroom workflows.

• Edit: Detect fields in forms and programmatically fill them. Build automated document completion pipelines without manual review.

Key Features:

• The most complete suite of document APIs that achieve 99+% accuracy on the toughest use cases

• Agentic OCR pipeline with intelligent routing through vision AI and custom-trained VLMs

• Composer background agent that automatically experiments with prompt and schema variants

• Comprehensive evaluation framework with automated accuracy reports, confidence scoring, human-in-the-loop review UI, and LLM-as-a-judge scoring

• Multiple performance modes for parsing with fast and cost-optimized parse options

Bottom Line:

Extend delivers near-human accuracy (95-99%+) on complex documents where traditional OCR fails. The agentic approach with Composer automatically optimizes schemas against evaluation sets, eliminating weeks of manual tuning and reducing time-to-production from months to days, while Review Agent QAs all extracted values to call out true confidence scoring based on semantic understanding.

The workflow orchestration and built-in review UI create a complete system for quality control, not just an extraction endpoint. Multiple processing modes let you optimize for latency, cost, or accuracy per use case rather than forcing one-size-fits-all performance. Proven in production by organizations like Brex, Zillow, Chime, and Square processing millions of mission-critical documents.

Extend is built for teams that need enterprise-grade accuracy, workflow control, continuous optimization, and production-ready infrastructure in a single API, not just OCR with manual tuning on top.

Nanonets

Nanonets provides an OCR and document extraction API that uses AI to process invoices, receipts, identity documents, and custom forms.

Key Features:

• Pre-trained models for common document types like invoices, receipts, and IDs with claimed 95%+ accuracy on standard formats

• Custom model training through UI-based annotation tools requiring 50-100 sample documents

• REST API with webhook support for async processing and job status polling

• Cloud-based deployment

Limitations:

Nanonets lacks comprehensive workflow orchestration, schema versioning, or built-in evaluation frameworks. Multi-step workflows require custom engineering since capabilities are bundled into a single endpoint, and the human review UI is limited, offering no granular field editing or feedback loops to continuously improve models.

Bottom Line:

Nanonets works for simple document extraction tasks, but Extend delivers the accuracy, agentic optimization, and production infrastructure needed for mission-critical workflows.

Pulse

Pulse is a document extraction service focused on converting PDFs, images, and office documents into markdown or HTML with optional structured JSON via schemas.

Key Features:

• Sync and async extraction endpoints with job polling

• Schema-based extraction

• Bounding box coordinates for extracted text

• Webhook configuration for job completion events

Limitations:

No evaluation sets or regression testing capabilities to measure accuracy over time or catch schema drift. No workflow orchestration beyond webhooks, requiring teams to build state machines externally. Missing schema versioning, dedicated classification API, human-in-the-loop review UI, and agentic optimization.

Bottom Line:

Pulse delivers extraction outputs, but Extend provides the full system for maintaining quality, managing schema evolution, and orchestrating complex document pipelines at scale.

Reducto

Reducto is an OCR API designed for document parsing and extraction with a focus on simplicity and developer experience.

Key Features:

• Document parsing with OCR capabilities

• Extraction API with schema support

• Cloud deployment with API access

• SOC2 and HIPAA compliance

Limitations:

Single processing mode for parsing, extraction, and splitting regardless of latency or cost requirements, forcing teams to overpay for batch workloads or under-serve real-time flows. No schema versioning, requiring risky changes directly in production. No evaluation framework, reports, or custom scoring to measure accuracy. No agentic capabilities for automated schema optimization, drift handling, or confidence scoring. Missing workflow orchestration, audit logs, version history, and human-in-the-loop review UI.

Bottom Line:

Reducto offers basic OCR functionality, but Extend delivers multiple performance modes, agentic optimization, comprehensive evaluation tooling, and enterprise controls required for production document pipelines.

LlamaIndex

LlamaIndex is a data framework for connecting custom data sources to AI applications, including document parsing and indexing capabilities.

Key Features:

• Document loaders for various file formats

• Integration with vector databases and embeddings

• Query interface for document retrieval

• Open-source framework with Python SDK

Limitations:

Not purpose-built for production document extraction, lacking specialized OCR accuracy, form filling, splitting, and classification APIs that document-intensive workflows require. No dedicated evaluation framework for measuring extraction accuracy or built-in human review interfaces. Requires significant custom engineering to achieve production-grade document processing compared to purpose-built APIs.

Bottom Line:

LlamaIndex excels at RAG infrastructure, but Extend delivers purpose-built document processing APIs with specialized accuracy, evaluation tooling, and workflow orchestration for mission-critical extraction at scale.

ABBYY

ABBYY provides enterprise OCR and document processing software with FineReader and FlexiCapture products offering document conversion and data capture capabilities.

Key Features:

• FineReader for PDF conversion and OCR

• FlexiCapture for data capture and extraction

• On-premises and cloud deployment options

• Support for multiple languages and document types

Limitations:

Legacy architecture requiring significant configuration and professional services rather than developer-first API integration. No agentic optimization, automated schema tuning, or continuous improvement loops. Multiple products require separate licenses and integrations. Missing built-in evaluation frameworks that enable rapid iteration. Higher total cost of ownership with complex licensing models compared to consumption-based API pricing.

Bottom Line:

ABBYY serves enterprise digitization needs, but Extend provides developer-friendly APIs with agentic automation, comprehensive tooling, and flexible deployment without the complexity or licensing overhead.

Feature Comparison Table of Document Processing APIs

Here's how the six document processing APIs compare on production-critical capabilities that determine whether you can reliably ship and maintain document workflows at scale.

Extend is the only solution that delivers all seven capabilities in a unified API, eliminating the need to build custom tooling for quality control, schema management, and workflow automation.

Why Extend Is the Best Document Processing API for Developers

When you're building document processing into production systems, you need more than just an extraction endpoint. You need the full stack: accuracy that handles edge cases, automated optimization that eliminates tuning overhead, evaluation tools that catch regressions, and workflow controls that adapt to changing requirements.

We built Extend specifically for this reality. The combination of agentic optimization, multiple performance modes, and schema versioning means you can ship fast without sacrificing quality or flexibility. You're not choosing between speed, cost, and accuracy. You're getting infrastructure that adapts to each use case.

The evaluation framework and review UI mean quality control is built in, not bolted on. You can measure accuracy, catch drift, and improve performance without building custom tooling. For developers shipping mission-critical document workflows, that's the difference between weeks of integration work and production-ready pipelines in days.

Final thoughts on document processing API selection

Production document workflows need more than basic OCR endpoints. A solid SDK integration for document processing means getting accuracy, automated optimization, and quality controls without building everything yourself. Extend gives you the complete toolkit so you can ship in days instead of months and keep improving as your documents evolve.

FAQ

How do I choose the right document processing API for my use case?

Start by evaluating accuracy requirements on your actual documents, then assess whether you need workflow orchestration, schema versioning, and evaluation tooling for production maintenance. If you're processing mission-critical documents where 90% accuracy isn't enough, prioritize APIs with agentic optimization and built-in quality control over basic OCR endpoints.

Which document processing API works best for teams without ML expertise?

Extend's Composer background Agent automatically optimizes schemas and handles edge cases without manual tuning, making it ideal for engineering teams that want production-grade accuracy without ML expertise. Alternatives like Nanonets or Pulse require more manual configuration and lack automated optimization capabilities.

Can I test different performance modes for latency versus cost optimization?

Extend provides separate fast, cost-optimized, and accuracy-optimized modes for parsing, extraction, and splitting, letting you configure per workflow. Most alternatives like Reducto or Pulse offer only single processing modes, forcing you to overpay for batch workloads or under-serve real-time requirements.

What's the difference between document extraction APIs and RAG frameworks?

Document extraction APIs like Extend are purpose-built for converting documents into structured data with specialized OCR, form filling, and classification capabilities. RAG frameworks like LlamaIndex focus on document indexing and retrieval for AI applications but require significant custom engineering to achieve production-grade extraction accuracy.

How long does it take to deploy a production document processing pipeline?

With Extend's agentic optimization and pre-trained models, teams typically achieve production-ready results in days versus the weeks or months required for manual tuning with other solutions. The built-in evaluation framework and schema versioning eliminate the custom tooling work that extends deployment timelines.