Meet Parse. Parse allows you to:

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

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

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

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 →
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 -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'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)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.