Cohere has unveiled Rerank 3, a new foundation model built to enhance enterprise search and Retrieval Augmented Generation (RAG) systems.
This new model from Cohere will change how businesses handle and access large amounts of data, improving search efficiency and accuracy. Rerank 3 integrates smoothly with any database, search index, and legacy applications with native search capabilities.
Its remarkable feature set includes a 4k context length, enabling superior search quality for longer documents, and the ability to search across multi-aspect and semi-structured data such as emails, invoices, JSON documents, code, and tables.
Moreover, with support for over 100 languages, Rerank 3 ensures robust multilingual performance, simplifying retrieval for diverse user bases.
One of the key highlights of Rerank 3 is its exceptional precision in semantic reranking, ensuring that only the most relevant information is delivered to generative models. This optimised approach not only enhances response accuracy but also keeps latency and costs at minimal levels, particularly beneficial when dealing with extensive data repositories.
Enterprise data is often complex and current systems have difficulty searching through multi-aspect and semi-structured data sources. Rerank 3 excels in ranking multi-aspect data, leveraging metadata fields to deliver comprehensive and accurate search results.
Its capabilities extend to code retrieval, facilitating productivity gains for engineering teams working with proprietary code repositories. Furthermore, Rerank 3 stands out with up to 3x improvements in latency at long context lengths compared to its predecessor.
Rerank 3 is supported natively in Elastic’s Inference API. This collaboration with Elastic signifies a strategic step towards empowering businesses with advanced search capabilities tailored to their complex data needs.
“We’re excited to be partnering with Cohere to help businesses unlock the potential of their data.” said Matt Riley, GVP & GM of Elasticsearch.
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