Parse messy documents into AI-ready context
Ragie Parse extracts structured context from real-world documents for agents, retrieval, and workflows.
OCR that understands document layout, not just text.
Agentic OCR
Ragie Parse performs OCR across messy PDFs, slides, and spreadsheets, including large files, inconsistent layouts, and low-quality scans common in production systems.
Structured Elements
Extracts structured elements—tables, forms, charts, key-value pairs, and signatures—instead of returning raw text. Output is immediately usable by applications and agents.
Accurate bounding boxes
Every extracted element includes precise bounding boxes that map it back to its exact location in the original document. This allows you to see exactly where a value came from, highlight it in the source file, and build systems that require traceability and auditability.
Ragie Parse handles complex document layouts across every element type.
Whether you're building agents, retrieval, or workflows, Ragie Parse handles complex documents across every element, preserving document structure and bounding boxes.
Tables
Extracts tables accurately while preserving rows, columns, and relationships.
Images and Charts
Identifies visual elements and associates them with surrounding context.
Grids
Understands grid-based layouts where structure defines meaning.
Form Fields
Detects labeled inputs, values, and field groupings in complex forms.
Key / Value
Extracts key-value pairs while preserving their semantic relationships.
Signatures
Identifies signatures and links them to their position and context in the document.
Stamps
Detects stamps and markings that often carry legal or operational significance.
Scanned Documents
Handles low-quality scans with layout-aware OCR and structure preservation.
Handwritten Notes
Extracts handwritten content while retaining its placement and context.
Large Spreadsheets
Parses large, messy spreadsheets without flattening or losing structure.
Video and Audio
Transcribes audio and detects visual scenes for structured downstream use.
Multilingual
Supports multilingual and RTL documents.
Enterprise-grade parsing that fits into your architecture.
Structured output,
no lock-in
Ragie Parse returns parsed elements as structured data. Store them, transform them, or index them in your own systems. Or, if it makes sense, continue into Ragie's indexing pipeline.
Amazon S3
Backblaze
Confluence
Dropbox
Freshdesk
Gmail
Amazon S3
Backblaze
Confluence
Dropbox
Freshdesk
Gmail
Google Cloud Storage
Google Drive
HubSpot
Intercom
Jira
Notion
Google Cloud Storage
Google Drive
HubSpot
Intercom
Jira
Notion
Production-ready connectors
Ragie’s connectors integrate Parse with your existing infrastructure, keeping parsed context synchronized as documents evolve. No manual uploads. No data migration.
