(ADE) is a document intelligence platform that converts documents into reliable, structured data. Use the structured data from ADE to build retrieval-augmented generation (RAG) applications, power intelligent search systems, extract key information, and automate document processing at scale.Documentation Index
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How ADE Works
provides multiple APIs for document processing: Parse, Extract, Classify, Section, and Split. Most workflows start with Parse, which converts your documents into structured data. After parsing, you can optionally use Extract to pull specific data fields, Section to generate a hierarchical table of contents, or Split to separate multi-document files. Use Classify independently to label pages by document type before or without parsing.| API | Description | When to Use |
|---|---|---|
| Parse | Converts documents into structured Markdown with hierarchical JSON. Identifies elements like text, tables, and form fields with exact page and coordinate references. | Use to convert documents into structured data for downstream applications, such as RAG, search, and training LLMs. This is the required first step for all ADE workflows. |
| Extract | Pulls specific data fields from parsed documents using schema-based extraction. | Use when you need the values for specific fields. Can be used after Parse or Split. |
| Classify | Assigns a category to each page of a document based on classes you define. | Use when you need to sort, route, or label pages by document type. Does not require Parse. |
| Section | Analyzes a parsed document and generates a hierarchical table of contents with section titles, levels, and chunk references. | Use when you need to navigate, scope, or retrieve content by section (for example, for section-aware RAG chunking or document review tools). |
| Split | Classifies and separates parsed documents into multiple sub-documents based on document types you define. | Use when one file contains multiple documents that need to be separated, such as batched Know Your Customer (KYC) documents. |
Get Started
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Key Features
Accurate results
Delivers high accuracy, even on complex documents. Achieved 99.16% accuracy on the DocVQA dataset.
Element detection
Identifies specific elements (called “chunks”) including text, tables, images, form fields, and bar codes.
Visual grounding
Includes page numbers and coordinates for each chunk to support traceability, validation, and compliance workflows.
Layout-agnostic parsing
Handles any document layout without templates or training—works out of the box.
Understands hierarchical relationships
Understands relationships between elements to generate accurate descriptions and maintain proper reading order.
Flexible output
Returns results in Markdown for human readability and JSON for programmatic access.
Supports multiple file types
Parses PDFs, images, text documents, presentations, and spreadsheets.
Supports multiple languages
Parses documents in multiple languages.