You're evaluating document processing platforms and comparing Extend vs Pulse to find the right fit for your architecture. Both platforms handle document extraction, but they take fundamentally different approaches to solving the problem. Pulse focuses on providing robust extraction endpoints with spatial references and flexible output formats. Extend delivers extraction as part of a complete document processing system that includes workflow orchestration, quality control, and continuous improvement infrastructure. Understanding these architectural differences will help you choose the platform that aligns with your team's capabilities and requirements.

TLDR:

• Extend delivers 95-99%+ extraction accuracy with built-in quality control and continuous improvement loops.

• You get workflow orchestration, schema versioning, and evaluation frameworks out of the box.

• Agentic array extraction handles thousands of items in tables without custom chunking logic.

• Pulse offers basic extraction endpoints; you build orchestration and quality control yourself.

• Extend is the complete document processing toolkit with the most accurate parsing, extraction, and splitting APIs to ship your hardest use cases in minutes.

Platform Overview

Extend: A end-to-end platform for building, iterating, evaluating, and deploying document processing infrastructure with best-in-class APIs for parsing, extraction, classification, and splitting, along with an integrated evaluation suite, schema/config versioning, human-in-the-loop Review UI, and an optimization agent (Composer).

Pulse: A document extraction service focused on just parsing PDFs, images, and office docs into markdown or HTML, with optional structured JSON via schemas, plus bounding boxes and webhooks/async jobs.

At-a-Glance Comparison

Extraction Accuracy and Quality Control

Extend

Quality control is built into the extraction pipeline. Accuracy is automatically benchmarked on your documents with field- and document-level reports. Each extracted field receives a confidence score that drives routing—low-confidence results are flagged by the Review Agent for human review.

The human-in-the-loop interface lets your team review flagged results, correct them, and approve outputs. Those corrections feed continuous improvement, increasing accuracy over time without rebuilding schemas.

Composer automatically tests prompt and schema configurations to deliver production-grade accuracy in minutes instead of weeks of manual tuning.

Pulse

Pulse returns extraction outputs with bounding box coordinates that trace each field back to its location in the source document. This gives you spatial references for where data originated. However, the service doesn't include testing or validation infrastructure. You'll need to build your own evaluation workflows to measure accuracy, maintain test sets, and run regression checks when you modify schemas.

Workflow Orchestration and Logic

Extend

Extend built workflow orchestration as a core feature. You can chain classification, splitting, parsing, extraction, evaluation, and review into end-to-end pipelines through an API. Each workflow step can branch based on confidence thresholds, document type, or custom business rules.

Classification and splitting act as first-class routing primitives. Documents get automatically separated, typed, and directed to appropriate extraction schemas without manual intervention. Low-confidence outputs automatically route to human review queues, while high-confidence results flow straight through to your downstream systems.

This eliminates the need to build and maintain external state machines or orchestration infrastructure. The entire pipeline runs inside the system with full traceability across every step.

Pulse

Pulse provides extraction endpoints with job polling and webhook capabilities. The service handles extraction as a single operation. If you need multi-step workflows that chain classification, splitting, extraction, and validation together, you'll need to build that orchestration layer yourself.

Conditional routing based on confidence scores or validation rules requires external state management. You'll need to stand up your own logic to direct documents down different processing paths or trigger human review when extraction quality drops below acceptable thresholds.

Schema Management and Versioning

Extend

Extend provides full schema lifecycle management with explicit versioning. You can test changes in draft mode, publish versions when ready, and pin workflows to specific schema versions for stability. Schema versioning prevents breaking changes when document templates evolve.

Composer optimizes configurations against evaluation sets and compares iterations to show performance differences. Composer also handles schema drift automatically. Composer will detect when a schema field is changed, auto-repair your labeled results to match the new schema, surface the re-mapping for you to review and approve. Configuration changes are gated by evaluation runs that measure accuracy impact before deployment. This approach reduces regression risk when templates drift or requirements change.

Pulse

Pulse supports schema extraction where you define the structure and receive structured JSON outputs. You can modify schemas between extraction jobs as needed. The service processes each request according to the schema provided at that time. Testing schema changes requires implementing separate comparison workflows outside the extraction service.

Large-Scale Document Processing

Extend

Extend's agentic array extraction handles thousands of items in tables and lists with configurable strategies for chunk sizes and merging logic. Semantic chunking breaks large documents into meaningful sections while maintaining correct model context throughout the entire document.

Intelligent LLM-based merging automatically resolves duplicates and conflicts that arise when data spans multiple pages or chunks. You don't need to build reconciliation logic or manage context windows manually.

Extend has fast extraction mode for latency-sensitive applications and cost-optimized modes for high-volume batch processing. This gives you direct control over performance versus economics trade-offs based on your specific use case requirements.

Pulse

Pulse processes structured JSON extractions across PDFs, Word, and Excel files with bounding box coordinate tracking. The service handles extraction requests as submitted, regardless of document size or complexity.

When you work with documents containing extensive arrays or multi-page tables spanning hundreds or thousands of items, you'll need to implement chunking logic, context management, and result reconciliation in your application layer. The extraction API doesn't include specialized handling for these scenarios, so organizations managing large-scale document volumes build custom pre-processing and post-processing pipelines around the core extraction endpoint.

Document Editing and Form Filling

Extend

Extend provides both read and write capabilities for complete document lifecycle automation. Their File Editing API enables programmatic document modification at scale.

Form field detection accurately identifies text inputs, checkboxes, radio buttons, signatures, and tables across complex layouts. Fast form editing processes long documents in seconds rather than minutes. Overflow logic automatically handles answers that span multiple lines or fields without breaking document layout.

This means you can extract data from incoming documents and populate completed forms as part of the same automated workflow. Organizations use this to process inbound documents, validate extracted data, and return completed forms to customers without manual intervention.

Pulse

Pulse focuses exclusively on extraction workflows that convert documents into markdown, HTML, or structured JSON. The service is designed for read-based operations that pull data out of documents for downstream use. If you need to modify documents or fill forms programmatically, you'll need to use separate tools alongside Pulse.

Why Extend is the Better Choice

The intelligent document processing market is projected to grow from $10.57 billion in 2025 to $66.68 billion in 2032, driven by organizations recognizing that extraction accuracy alone is insufficient for mission-critical workflows. 88% of financial institutions are prioritizing document automation in their digital transformation plans for 2025, requiring complete systems for quality assurance, workflow control, and continuous improvement.

Pulse works as a straightforward extraction endpoint. You send documents, receive structured outputs, and build everything else yourself. That approach makes sense for simple use cases where you have engineering resources to construct orchestration layers, evaluation frameworks, and quality control systems.

Extend is built for teams that need production document processing infrastructure, not just extraction results. The difference becomes critical when you need to catch regressions before deployment, route documents intelligently based on confidence, or improve accuracy through feedback loops. These capabilities work together as a cohesive system rather than requiring you to stitch together multiple tools.

Organizations processing mission-critical documents choose Extend because extraction is just the starting point. The surrounding infrastructure determines whether your document workflows actually ship and stay reliable at scale.

Final Thoughts on Extend vs Pulse

Extend vs Pulse isn't about which parsing API is better, it's about whether you need infrastructure or just endpoints. Pulse gives you document-to-JSON conversion, and you build the rest. Extend gives you the complete system with evaluation, orchestration, and quality control built in. Your choice depends on whether you want to spend time building infrastructure or shipping document workflows.

FAQ

How should I decide between Extend and Pulse for my document processing needs?

Choose Pulse if you need basic extraction endpoints and have engineering resources to build orchestration, evaluation, and quality control systems yourself. Choose Extend if you're processing mission-critical documents that require built-in accuracy benchmarking, confidence-based routing, human review workflows, and continuous improvement loops without building infrastructure from scratch.

What's the main difference in how Extend and Pulse handle extraction quality?

Pulse returns extraction outputs with bounding boxes but requires you to build your own testing and validation infrastructure. Extend includes automated evaluation frameworks, field-level confidence scoring, Review Agent for flagging low-confidence outputs, and Composer AI that automatically optimizes schemas to reach production-grade accuracy in minutes.

Who is Pulse best suited for versus Extend?

Pulse works well for teams with simple parsing use cases and engineering capacity to construct surrounding infrastructure. Extend is built for technical teams at organizations processing high volumes of mission-critical documents who need production-ready infrastructure including classification, splitting, evaluation, human-in-the-loop review, and workflow orchestration as part of the core system.

Can Extend handle documents with thousands of line items or multi-page tables?

Yes. Extend's agentic array extraction processes thousands of items with semantic chunking that maintains context across pages and intelligent LLM-based merging that resolves duplicates and conflicts automatically, eliminating the need to build custom reconciliation logic.

What happens when I need to modify my extraction schemas after deployment?

Extend provides schema versioning that lets you test changes in draft mode, compare accuracy against evaluation sets, and pin workflows to specific versions for stability. Composer gates configuration changes with evaluation runs that measure accuracy impact before deployment, reducing regression risk when templates evolve.