Introducing Command R+: Our new, most powerful model in the Command R family.
A major provider of SaaS workforce collaboration and productivity tools wanted to improve its search capabilities. Its customers were often frustrated trying to find documents with its legacy search tools.
A major provider of SaaS workforce collaboration and productivity tools wanted to improve its search capabilities. Its customers were often frustrated trying to find documents with its legacy search tools.
Cohere Rerank was integrated into the company’s search infrastructure. Rerank ingested the output of the existing search tools, reordering the responses based on relevance to the user’s search query, resulting in far more relevant answers and higher customer satisfaction.
Cohere Rerank was integrated into the company’s search infrastructure. Rerank ingested the output of the existing search tools, reordering the responses based on relevance to the user’s search query, resulting in far more relevant answers and higher customer satisfaction.
STEP 1.
Existing lexical and semantic search tools are queried with the user search term
STEP 2.
Cohere Rerank embeds the original query and search results in real time
STEP 3.
Rerank returns matches re-ordered by semantic relevance to the original query, with relevance scores
Improved search relevance
Improved user satisfaction
Fast time to live; easy to integrate
Cohere’s embedding prioritizes accurate reranking, even with noisy datasets
Cohere’s models come with connectors to common data sources
Cohere’s models can be fine-tuned to further improve domain performance
Cohere’s powerful inference frameworks optimize throughput and reduce compute requirements
Cohere models can be accessed through a SaaS API, on cloud infrastructure (Amazon SageMaker, Amazon Bedrock, OCI Data Science, Google Vertex AI, Azure AI), and private deployments (virtual private cloud and on-premises)
Over 100 languages are supported, so the same topics, products, and issues are identified the same way