Cohere Compass vs. Cohere Embed Comparison


Cohere Compass Cohere AI	Cohere Embed Cohere	+	+
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About Cohere Compass is an intelligent enterprise search and discovery system that connects agents and models to business data, giving AI applications the context they need through powerful search and retrieval. It uses advanced extraction processes and AI-powered indexing to surface relevant information from enterprise documents with high accuracy. Compass is multimodal, multilingual, and format-agnostic, allowing it to understand images, slides, spreadsheets, PDFs, DOCX files, XLSX files, and other document types. It can connect to existing data sources or accept local document uploads, then automatically process, index, and manage that information without requiring teams to host or scale their own vector database. It is built on Cohere’s Embed and Rerank retrieval models and can support AI agents, retrieval-augmented generation applications, and unified enterprise knowledge search.	About Cohere's Embed is a leading multimodal embedding platform designed to transform text, images, or a combination of both into high-quality vector representations. These embeddings are optimized for semantic search, retrieval-augmented generation, classification, clustering, and agentic AI applications. The latest model, embed-v4.0, supports mixed-modality inputs, allowing users to combine text and images into a single embedding. It offers Matryoshka embeddings with configurable dimensions of 256, 512, 1024, or 1536, enabling flexibility in balancing performance and resource usage. With a context length of up to 128,000 tokens, embed-v4.0 is well-suited for processing large documents and complex data structures. It also supports compressed embedding types, including float, int8, uint8, binary, and ubinary, facilitating efficient storage and faster retrieval in vector databases. Multilingual support spans over 100 languages, making it a versatile tool for global applications.
Platforms Supported Windows Not Supported Mac Not Supported Linux Not Supported Cloud Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported	Platforms Supported Windows Not Supported Mac Not Supported Linux Not Supported Cloud Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported
Audience Developers, AI teams, and enterprises seeking to connect agents and applications to internal data through secure, scalable search and retrieval	Audience AI teams seeking a solution for generating high-quality, multimodal embeddings that enhance search accuracy and contextual understanding
Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported	Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported
API Offers API Not Supported	API Offers API Not Supported
Screenshots and Videos View more images or videos	Screenshots and Videos View more images or videos
Pricing No information available. Free Version Supported Free Trial Not Supported	Pricing $0.47 per image Free Version Not Supported Free Trial Not Supported
Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software	Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software

Training Documentation Supported Webinars Supported Live Online Supported In Person Not Supported	Training Documentation Supported Webinars Supported Live Online Supported In Person Not Supported
Company Information Cohere AI Founded: 2019 Canada cohere.com/compass	Company Information Cohere Founded: 2019 Canada cohere.com/embed
Alternatives No Alternatives	Alternatives Codestral Embed Mistral AI
	voyage-code-3 MongoDB
	voyage-3-large MongoDB
	Mixedbread
View All	Gemini Embedding 2 Google View All
Categories Retrieval-Augmented Generation (RAG) Supported	Categories Embedding Models Supported Retrieval-Augmented Generation (RAG) Supported

Integrations Cohere Not Supported GitHub Supported Gmail Supported Google Drive Supported Jira Supported Linear Supported Microsoft Exchange Supported Microsoft OneDrive Supported Microsoft Outlook Supported Microsoft SharePoint Supported Model Context Protocol (MCP) Supported Notion Supported Salesforce Supported Slack Supported voyage-4-large Not Supported Show More Integrations View All 13 Integrations	Integrations Cohere Supported GitHub Not Supported Gmail Not Supported Google Drive Not Supported Jira Not Supported Linear Not Supported Microsoft Exchange Not Supported Microsoft OneDrive Not Supported Microsoft Outlook Not Supported Microsoft SharePoint Not Supported Model Context Protocol (MCP) Not Supported Notion Not Supported Salesforce Not Supported Slack Not Supported voyage-4-large Supported Show More Integrations View All 2 Integrations
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