Parse | Turn Any Document into Structured Data | Reducto

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APIs Overview

/parse

Use when: Structured content from any document is needed for LLM or RAG use.

Output: Structured chunks with typed blocks, bounding boxes, and confidence scores.

Read the Parse docs

/extract

Use when: The fields to pull are defined and typed JSON is needed.

Output: Schema-typed JSON with optional citations on every value.

/split

Use when: One file contains multiple logical documents or sections.

Output: Page ranges for each section, with confidence scores.

/classify

Use when: Files need to be routed by type before processing.

Output: Best-matching category with per-criterion confidence.

/edit

Use when: A PDF form needs filling or a DOCX needs updating.

Output: A downloadable edited file, plus a reusable form schema.

Features

  1. Preserves the original layout
    Multi-column layouts, headers, footnotes, sidebars, and multi-page tables. Reading order stays intact.

  2. Citation-grounded output
    Every block includes a bounding box and confidence score. Trace any output back to its exact location.

  3. Agentic OCR for hard scans
    A VLM review pass corrects handwriting, faded scans, unusual fonts, and misaligned columns.

  4. Table fidelity that holds up
    Merged cells, nested headers, multi-page tables reconstruct in HTML, Markdown, JSON, or CSV.

  5. Sync and async, your call
    Sync for low-latency calls, async with webhooks for batch jobs. Files up to 5GB via presigned URL.

Step-by-step Process

  1. Send a file
    Upload via /upload or pass a public or presigned URL directly. Supports PDFs, images, Office documents, and spreadsheets.

  2. We read the page
    Vision models recognize titles, paragraphs, tables, figures, headers, and footers.

  3. We reconstruct structure
    Tables, merged cells, and figures rebuild faithfully. Agentic review handles complex pages.

  4. You get JSON back
    Chunks with typed blocks and bounding boxes, optimized for RAG and LLM workflows.

Read the full Parse reference in the docs

Proven Performance

5B+ pages processed

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