OCR for scanned and digital files
Parse extracts text from scanned and digital documents using OCR, which makes it suitable for files that are not natively machine-readable.
Parse
Parse is Cohere’s document parsing model for enterprise documents, tables, and images. It turns unstructured content into structured, AI-ready data for search and agent workflows.
Overview
Parse is Cohere’s document parsing model for enterprise documents, tables, and images. It converts unstructured content into structured data that AI systems can search, index, or act on.
The product is positioned for organizations that need document ingestion for search and agents, with support for OCR, visual reasoning, bounding boxes, multilingual documents, and deployment across cloud, on-premises, private, and air-gapped environments.
Core capabilities
Multimodal document parsing
The model detects tables, diagrams, and images embedded in complex documents so those elements can be carried into downstream AI workflows with more context.
Visual grounding with page coordinates
Parse returns axis-aligned bounding boxes as page coordinates and can highlight key visual regions for source attribution and spatial reasoning.
Multilingual document support
The model supports major commercial languages and is described as multilingual, helping teams process mixed-language enterprise document sets.
Enterprise deployment options
Parse can be deployed in the cloud, on-premises, or in private and air-gapped environments to match different security and infrastructure requirements.
Practical use cases
Document processing workflows
Teams can automate ingestion and extraction from high-volume files such as claims, contracts, and invoices, reducing the amount of manual review and data entry required.
Semantic search preparation
Organizations can turn complex documents into retrieval-ready representations that support chunking, indexing, search, and citation quality in enterprise search systems.
Multimodal agent workflows
AI agents can use Parse output to reason over complete document context, including tables, diagrams, and other visual elements, instead of relying on plain text alone.
Controlled enterprise deployment
Enterprises that need tighter control over data and infrastructure can deploy Parse in private, on-premises, or air-gapped environments.
Multilingual document intake
Teams working with multilingual document sets can use Parse to process content in major commercial languages with consistent output.
Pros and Cons
Pros
- Supports OCR and visual reasoning, which helps Parse handle both text and visual structure in documents.
- Returns bounding boxes for extracted content, which is useful for highlighting and citation workflows.
- Supports multilingual document processing across nine commercial languages.
- Can be deployed in cloud, on-premises, private, or air-gapped environments.
- Has a published benchmarking framework, ParseBench, that explains how parsing quality is evaluated.
Cons
- The page does not provide a complete technical specification for every supported input type, output schema, or validation rule.
- Some integration details are only stated at a high level, so readers may still need product documentation or sales contact for workflow specifics.
FAQ
What is Parse?
Parse is Cohere’s document vision parsing model. It is designed to turn unstructured content in enterprise documents and images into structured data that downstream AI agents and applications can use.
Does Parse support OCR?
Yes. The page states that Parse supports OCR as well as visual reasoning, so it can extract text while also understanding visual elements and context.
Where can Parse be used?
Parse is available through the Cohere API and Model Vault, and it can also be used on Amazon SageMaker and Microsoft Azure. The page also says it can be deployed privately for enterprise use cases that need more control over data and infrastructure.
What is ParseBench?
ParseBench is Cohere’s benchmark for document parsing quality across Tables, Text Content, Text Formatting, Layout, and Charts. The page says Cohere reports results for Tables, Text Content, and Text Formatting, while Layout and Chart scores are excluded because they cover capabilities outside the current product scope.
Is Parse multilingual?
Yes. Parse is described as a multilingual model trained on nine of the world’s most prevalent commercial languages.
Quick Facts
- Category
- Document parsing / document vision
- Product line
- Cohere Parse
- Access
- Cohere API, Model Vault, Amazon SageMaker, Microsoft Azure
- Deployment
- Cloud, on-premises, private, and air-gapped environments
- Languages
- Nine major commercial languages
- Related product
- Compass includes Parse as one component in its document processing pipeline
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