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Parse converts documents into structured data. It identifies text blocks, tables, figures, headers, and key-value pairs, returning everything as markdown with coordinates for each element. The output is designed for downstream processing—whether that’s feeding an LLM, building a search index, or piping into Extract for structured data extraction.
Example Parse Pipeline

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What Parse extracts

Parse breaks your document into chunks, each representing a semantic unit of content:
  • Text blocks: Paragraphs and body text, preserving reading order across columns
  • Tables: Structured data with rows and columns, output as markdown, HTML, or JSON
  • Figures: Images, charts, and diagrams with optional AI-generated descriptions
  • Headers: Section titles with hierarchy levels for document structure
  • Key-value pairs: Form-like content where a label maps to a value
  • Footers: Page numbers, disclaimers, and repeated bottom-of-page content
Each chunk includes bounding box coordinates linking it back to its source location. In Studio, these appear as colored overlays on your document:
Bounding box colors
Click any box to jump to its output, or click output text to highlight its source.

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When to adjust configurations

The default configuration handles most documents well. The Configurations tab contains the whole list of available configurations, split into 5 buckets: Enhance — Enable agentic processing when results aren’t parsing correctly or text has OCR errors. Agentic adds a vision model pass to verify and correct processing results. This increases accuracy, but also cost and latency. Retrieval — Configure chunking for RAG pipelines. The default may produce segments too large or small for your embedding model. Set chunking mode to variable with a target size around 500-1000 characters. Formatting — Control output structure. Switch table format to html or json for programmatic use. Formatting also includes configurations for detecting attributes like change tracking, hyperlinks, highlights, and more. Spreadsheet — Handle Excel and CSV files. Control inclusions of cell colors, formulas, dropdowns, and hidden items in your outputs, as well as table clustering detection. Settings — Core processing controls such as specifying page ranges, returning images, and forcing a URL result. See Parse Configurations for the complete reference.

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Working with results

The Results tab shows parsed output as formatted markdown by default. The toolbar offers several options:
  • Copy — Copy the output to your clipboard
  • Download — Save results as a file
  • JSON — Toggle to see the raw API response structure
The JSON view is useful for understanding exactly what your code will receive. Each chunk includes: 
{
  "type": "text",
  "content": "Your extracted text here...",
  "bbox": {
    "left": 0.05,
    "top": 0.12,
    "width": 0.4,
    "height": 0.03,
    "page": 0
  }
}
Bounding boxes use normalized coordinates (0-1 range relative to page dimensions), making them consistent across different document sizes.

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Processing multiple files

Studio supports batch processing. Add multiple files using the Add file button in the file carousel, then check All Files before clicking Run to process the entire batch with your current configuration. This is helpful for testing configurations across a representative sample before deploying. If results vary significantly across documents, you may need to adjust settings or consider whether a single pipeline can handle your document variety.

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From Parse to Extract

Parse alone gives you the document’s content and structure. If you need specific fields—invoice totals, contract dates, patient names—add an Extract step. Click Add in the pipeline header to chain Parse → Extract, creating a multi-step pipeline you can deploy with a single Pipeline ID. See Extract Pipeline for schema configuration.

Parse API

API reference and response schema.

Parse Configurations

All configuration options with examples.