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What is Cohere Embed?

Cohere's Embed emerges as a leading multimodal embedding solution that adeptly transforms text, images, or a combination of the two into superior vector representations. These vector embeddings are designed for a multitude of uses, including semantic search, retrieval-augmented generation, classification, clustering, and autonomous AI applications. The latest iteration, embed-v4.0, enhances functionality by enabling the processing of mixed-modality inputs, allowing users to generate a cohesive embedding that incorporates both text and images. It includes Matryoshka embeddings that can be customized in dimensions of 256, 512, 1024, or 1536, giving users the ability to fine-tune performance in relation to resource consumption. With a context length that supports up to 128,000 tokens, embed-v4.0 is particularly effective at managing large documents and complex data formats. Additionally, it accommodates various compressed embedding types such as float, int8, uint8, binary, and ubinary, which aid in efficient storage solutions and quick retrieval in vector databases. Its multilingual support spans over 100 languages, making it an incredibly versatile tool for global applications. As a result, users can utilize this platform to efficiently manage a wide array of datasets, all while upholding high performance standards. This versatility ensures that it remains relevant in a rapidly evolving technological landscape.

What is Cohere Compass?

Cohere Compass operates as an advanced platform for enterprise search and discovery, seamlessly connecting agents and models with business data to provide AI applications with crucial contextual information through powerful search and retrieval functions. By utilizing advanced extraction methods alongside AI-enhanced indexing, it proficiently identifies and delivers relevant insights from enterprise documents with exceptional accuracy. The platform is designed to be multimodal, multilingual, and independent of specific formats, allowing it to interpret a wide range of document types, such as images, presentations, spreadsheets, PDFs, DOCX, and XLSX files. Additionally, it accommodates integration with existing data sources or supports local document uploads, streamlining the automatic processing, indexing, and management of that data without requiring teams to develop or scale their own vector database infrastructure. Leveraging Cohere’s Embed and Rerank retrieval models, Compass not only aids AI agents and retrieval-augmented generation applications but also promotes a unified approach to enterprise knowledge search, thereby boosting collaboration and informed decision-making throughout the organization. The adaptability and effectiveness of this platform make it a critical asset for businesses looking to maximize their data's potential. Ultimately, its capabilities ensure that organizations can navigate their vast data landscapes with confidence and efficiency.

Media

Media

Integrations Supported

Cohere
voyage-4-large

Integrations Supported

GitHub
Gmail
Google Drive
Jira
Linear
Microsoft Exchange
Microsoft OneDrive
Microsoft Outlook
Microsoft SharePoint
Model Context Protocol (MCP)
Notion
Salesforce
Slack

API Availability

API Availability

Pricing Information

$0.47 per image

Pricing Information

Pricing not provided
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training

Training Options

Documentation Hub
Webinars
Online Training

Company Facts

Organization Name

Cohere

Date Founded

2019

Company Location

Canada

Company Website

cohere.com/embed

Company Facts

Organization Name

Cohere AI

Date Founded

2019

Company Location

Canada

Company Website

cohere.com/compass

Categories and Features

Categories and Features

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