Introducing Command R+: Our new, most powerful model in the Command R family.
CHALLENGE
Multinational online retailers often struggle to act on product feedback. Products are often launched in multiple countries simultaneously, and synthesizing feedback across multiple languages can be difficult, time-consuming, and it’s easy to miss issues.
CHALLENGE
Multinational online retailers often struggle to act on product feedback. Products are often launched in multiple countries simultaneously, and synthesizing feedback across multiple languages can be difficult, time-consuming, and it’s easy to miss issues.
SOLUTION
Using Cohere Embed, retailers can build tools that can ingest text from support tickets, reviews, and third-party sources in over 100 languages. It can cluster by different attributes and name those clusters across languages giving retailers insights into feedback without extensive analysis or translation effort.
SOLUTION
Using Cohere Embed, retailers can build tools that can ingest text from support tickets, reviews, and third-party sources in over 100 languages. It can cluster by different attributes and name those clusters across languages giving retailers insights into feedback without extensive analysis or translation effort.
How it works
STEP 1.
Cohere Embed processes input text and stores it in a vector database
STEP 2.
Embeddings are clustered, classified, and named
STEP 3.
Clusters are visualized, giving users content information, names, and trends across multiple languages
Impact
Fast identification of trends
Multilingual analysts not required
Brand protection
The Cohere Difference
Leading model accuracy
Cohere’s retrieval performance ensures accurate responses and source citations.
Accelerated enterprise deployment
Cohere models come with connectors to common data sources
Customization
Our models can be fine-tuned to further improve domain performance
Flexible deployment
Cohere models can be accessed through a SaaS API, on cloud infrastructure (Amazon SageMaker, Amazon Bedrock, OCI Data Science, Google Cloud Platform, Azure AI), and private deployments (virtual private cloud and on-premises)
Multilingual support
Over 100 languages are supported, so the same topics, products, and issues are identified the same way