Benchmarks: Answer 99.16% of DocVQA Without Images in QA: Agentic Document ExtractionRead more

Parse any document to make it computable

Meet Parse. Parse allows you to:

  • Convert documents into accurate machine-readable formats.
  • Preserve the document hierarchy and layout.
  • Obtain precise citations for each content block and table cell.

Your account comes with enough credits to Parse several hundred pages.

The Problem

Common Parsing Challenges

Developing and maintaining a template for each document layout is labor intensive, error-prone and not scalable.

Processes developed for clean PDFs cannot handle blur, distortion and rotation in document scans and photographs.

Users complete form fields and mark checkboxes in inconsistent ways - not always staying within the lines!

Visual media such as graphs, flowcharts, illustrations and diagrams is either ignored or requires separate logic.

The Solution

Not all document parsers created equal.

High-quality parsing goes beyond basic OCR, which only turns pixels into text. To make a document truly computable, the parser must understand what each section means and how sections relate. ADE Parse adds a cognitive layer that reasons over documents — returning spatial relationships, visual grounding, and parsing confidences reliably at scale.

Accuracy on complex docs

Proven on real-world layouts, complex tables, and multi-page documents delivering consistent results in production, not just in benchmarks.

Accuracy on complex docs

Results come with proof

Verify parsed results with page numbers and precise coordinates for each chunk. Confidence scoring surfaces results that may need human review.

Results come with proof

Unmatched speed & scale

Eliminate processing bottlenecks and scale effortlessly. ADE handles thousands of pages per minute.

Unmatched speed & scale

What you get

  • No fine-tuning or templates required
  • Agentic system that plans and executes
  • Developer-friendly APIs
  • Returns clean Markdown and JSON
  • Layout and reading order detection
  • Supports many filetypes
  • Works across languages
  • Handles files up to 1 GB
  • Detects signatures and handwriting
  • Recognizes checkboxes on forms
  • Reconstructs messy tables
  • Enriches diagrams and figures
  • Assigns confidence scores
  • Returns bounding box coordinates
  • Fully managed SaaS or VPC
  • Real-time or batch processing
Document gallery

Built for complex, real-world documents.

Parse is made for complex, real-world documents. It can handle your massive tables, scientific charts, handwritten forms, poor quality faxes, and much more.

Read the Docs for Parse →
Sample documents parsed by ADE
UI and API

Prototype in the UI. Scale with the API.

Use the Agentic Document Extraction Visual Playground for rapid prototyping and experimentation. Then transition seamlessly to the REST API, Python library, or TypeScript library for your production workloads.

Provide our Agent Skills directly to agentic coding assistants to accelerate your development.

cURL
curl -X POST 'https://api.ade.landing.ai/v2/parse' \
  -H 'Authorization: Bearer YOUR_API_KEY' \
  -F 'document=@document.pdf' \
  -F 'model=dpt-3-pro-latest'
Python
from landingai_ade import LandingAIADE
client = LandingAIADE()

# Replace with your file path
response = client.parse(
    document=Path("/path/to/file/document"),
    model="dpt-2-latest",
    save_to="./output"
)
print(response.chunks)

Connect your AI Coding Tools to ADE Parse with MCP and Skills

Resource Center

Get Hands-on with Parse

  • Learn how to parse your large documents
  • Learn how to overlay bounding boxes on the original document
  • Learn how to interpret and use confidence scores
  • And much more

Frequently asked questions

A Document Pre-Trained Transformer (DPT) is the model that powers the parsing capabilities of the ADE Parsing APIs. The DPT identifies document layouts and chunks, then generates descriptive explanations (captions) for those chunks. All foundational DPT models are developed in-house by Landing AI by applying deep learning architectures. The T in DPT indicates that the model uses a Transformer architecture.

Start parsing documents in minutes.

Free tier available. No credit card required.