Cohere Parse turns enterprise documents into structured data

Cohere Parse is a document vision parsing model designed to convert complex documents, tables, images, and scanned files into structured data that AI systems can search or act on. The model supports high-fidelity OCR for scanned and digital documents, multimodal parsing for tables, diagrams, and embedded images, and visual grounding through precise bounding boxes for extracted content.

The product is positioned for enterprise document processing pipelines, including claims, contracts, invoices, semantic search, and multimodal agent workflows. Parse can transform documents into retrieval-optimized representations that improve chunking, indexing, search, and citation quality, while giving agents access to document context such as tables, diagrams, and visual regions.

Parse is available through the Cohere API and Model Vault, as well as on Amazon SageMaker and Microsoft Azure. It can also be deployed in the cloud, on-premises, or in private and air-gapped environments for organizations with specific cost, security, data control, or infrastructure requirements.

Cohere evaluates parsing quality with ParseBench across five dimensions: Tables, Text Content, Text Formatting, Layout, and Charts. Reported results focus on Tables, Text Content, and Text Formatting, while Layout and Chart scores are excluded because they cover capabilities outside the current product scope. Parse is trained on nine of the world’s most prevalent commercial languages.