+
+

Related Products

  • LM-Kit.NET
    29 Ratings
    Visit Website
  • Gemini Enterprise Agent Platform
    1,161 Ratings
    Visit Website
  • Couchbase
    417 Ratings
    Visit Website
  • Haast
    5 Ratings
    Visit Website
  • RaimaDB
    12 Ratings
    Visit Website
  • ScreenMeet
    35 Ratings
    Visit Website
  • Wallester
    277 Ratings
    Visit Website
  • Visual Lease
    450 Ratings
    Visit Website
  • FISPAN
    5 Ratings
    Visit Website
  • Framnex
    1 Rating
    Visit Website

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.

About

Improve your embedding metadata and embedding tokens with a user-friendly UI. Seamlessly apply advanced NLP cleansing techniques like TF-IDF, normalize, and enrich your embedding tokens, improving efficiency and accuracy in your LLM-related applications. Optimize the relevance of the content you get back from a vector database, intelligently splitting or merging the content based on its structure and adding void or hidden tokens, making chunks even more semantically coherent. Get full control over your data, effortlessly deploying Embedditor locally on your PC or in your dedicated enterprise cloud or on-premises environment. Applying Embedditor advanced cleansing techniques to filter out embedding irrelevant tokens like stop-words, punctuations, and low-relevant frequent words, you can save up to 40% on the cost of embedding and vector storage while getting better search results.

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

AI teams seeking a solution for generating high-quality, multimodal embeddings that enhance search accuracy and contextual understanding

Audience

Anyone searching for an open-source platform that helps them get the most out of your vector search

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

Screenshots and Videos

Pricing

$0.47 per image
Free Version Not Supported
Free Trial Not Supported

Pricing

No information available.
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 Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

Cohere
Founded: 2019
Canada
cohere.com/embed

Company Information

Embedditor
embedditor.ai/

Alternatives

Codestral Embed

Codestral Embed

Mistral AI

Alternatives

Cohere

Cohere

Cohere AI
Voyage AI

Voyage AI

MongoDB

Categories

Categories

Neural Search Supported
Semantic Search Supported

Integrations

Cohere Supported
Docker Not Supported
GitHub Not Supported
IngestAI Not Supported
voyage-4-large Supported

Integrations

Cohere Not Supported
Docker Supported
GitHub Supported
IngestAI Supported
voyage-4-large Not Supported
Claim Cohere Embed and update features and information
Claim Cohere Embed and update features and information
Claim Embedditor and update features and information
Claim Embedditor and update features and information