Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Cohere Compass serves as a smart enterprise search and discovery platform that links agents and models with business data, equipping AI applications with essential context via robust search and retrieval capabilities. Employing sophisticated extraction techniques along with AI-driven indexing, it effectively identifies and presents pertinent information from enterprise documents with remarkable precision. The system is designed to be multimodal, multilingual, and agnostic to formats, enabling it to comprehend various types of documents, including images, slides, spreadsheets, PDFs, DOCX, and XLSX files. Furthermore, it can integrate with existing data sources or allow for local document uploads, automatically processing, indexing, and managing that information without the need for teams to maintain or scale their own vector database infrastructure. Built on Cohere’s Embed and Rerank retrieval models, Compass not only supports AI agents and retrieval-augmented generation applications but also facilitates a cohesive approach to enterprise knowledge search, enhancing collaboration and decision-making across the organization. Its versatility and efficiency make it an invaluable tool for businesses aiming to leverage their data effectively.
Description
Cohere's Embed stands out as a premier multimodal embedding platform that effectively converts text, images, or a blend of both into high-quality vector representations. These vector embeddings are specifically tailored for various applications such as semantic search, retrieval-augmented generation, classification, clustering, and agentic AI. The newest version, embed-v4.0, introduces the capability to handle mixed-modality inputs, permitting users to create a unified embedding from both text and images. It features Matryoshka embeddings that can be adjusted in dimensions of 256, 512, 1024, or 1536, providing users with the flexibility to optimize performance against resource usage. With a context length that accommodates up to 128,000 tokens, embed-v4.0 excels in managing extensive documents and intricate data formats. Moreover, it supports various compressed embedding types such as float, int8, uint8, binary, and ubinary, which contributes to efficient storage solutions and expedites retrieval in vector databases. Its multilingual capabilities encompass over 100 languages, positioning it as a highly adaptable tool for applications across the globe. Consequently, users can leverage this platform to handle diverse datasets effectively while maintaining performance efficiency.
API Access
Has API
No
API Access
Has API
No
Integrations
Cohere
No
GitHub
Yes
Gmail
Yes
Google Drive
Yes
Jira
Yes
Linear
Yes
Microsoft Exchange
Yes
Microsoft OneDrive
Yes
Microsoft Outlook
Yes
Microsoft SharePoint
Yes
Integrations
Cohere
Yes
GitHub
No
Gmail
No
Google Drive
No
Jira
No
Linear
No
Microsoft Exchange
No
Microsoft OneDrive
No
Microsoft Outlook
No
Microsoft SharePoint
No
Pricing Details
No price information available.
Free Trial
No
Free Version
Yes
Pricing Details
$0.47 per image
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Cohere AI
Founded
2019
Country
Canada
Website
cohere.com/compass
Vendor Details
Company Name
Cohere
Founded
2019
Country
Canada
Website
cohere.com/embed