--- title: Build financial search applications using the Amazon... description: Learn how to build financial search applications using the Amazon Bedrock Cohere multilingual embedding model. Text embeddings capture the meaning of... canonical: https://daily.dev/posts/build-financial-search-applications-using-the-amazon-bedrock-cohere-multilingual-embedding-model-wfbgdkrs8 twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Build financial search applications using the Amazon Bedrock Cohere multilingual embedding model | daily.dev og:description: Learn how to build financial search applications using the Amazon Bedrock Cohere multilingual embedding model. Text embeddings capture the meaning of... og:url: https://daily.dev/posts/build-financial-search-applications-using-the-amazon-bedrock-cohere-multilingual-embedding-model-wfbgdkrs8 og:image: https://api.daily.dev/og/posts/WFBGDkRS8.png og:image:alt: Build financial search applications using the Amazon Bedrock Cohere multilingual embedding model og:image:width: 1200 og:image:height: 630 og:locale: en --- [AWS](https://daily.dev/sources/aws) [Read post](https://api.daily.dev/r/WFBGDkRS8) # [Build financial search applications using the Amazon Bedrock Cohere multilingual embedding model](https://api.daily.dev/r/WFBGDkRS8 "Go to post") Learn how to build financial search applications using the Amazon Bedrock Cohere multilingual embedding model. Text embeddings capture the meaning of unstructured data and enable applications such as semantic search, Retrieval Augmented Generation (RAG), topic modeling, and text classification. Cohere's multilingual embedding model groups text with similar meanings, supports multiple languages, and provides cost-efficient data compression. The Rerank endpoint enhances search results by introducing semantic search technology. [#aws](/tags/aws "Check all #aws posts")[#genai](/tags/genai "Check all #genai posts")[#amazon-bedrock](/tags/amazon-bedrock "Check all #amazon-bedrock posts")[#cohere](/tags/cohere "Check all #cohere posts") Jan 12, 2024•12m read time•From [aws.amazon.com](https://api.daily.dev/r/WFBGDkRS8 "aws.amazon.com") [](https://api.daily.dev/r/WFBGDkRS8 "Go to post") Table of contents [Cohere’s multilingual embedding model](https://api.daily.dev/r/WFBGDkRS8 "Cohere’s multilingual embedding model")[Use cases for text embedding](https://api.daily.dev/r/WFBGDkRS8 "Use cases for text embedding")[Enhanced search systems with Rerank](https://api.daily.dev/r/WFBGDkRS8 "Enhanced search systems with Rerank")[Solution overview](https://api.daily.dev/r/WFBGDkRS8 "Solution overview")[Enable model access through Amazon Bedrock](https://api.daily.dev/r/WFBGDkRS8 "Enable model access through Amazon Bedrock")[Install packages and import modules](https://api.daily.dev/r/WFBGDkRS8 "Install packages and import modules")[Import documents](https://api.daily.dev/r/WFBGDkRS8 "Import documents")[Select a list of documents to query](https://api.daily.dev/r/WFBGDkRS8 "Select a list of documents to query")[Embed and index documents](https://api.daily.dev/r/WFBGDkRS8 "Embed and index documents")[Build a retrieval system](https://api.daily.dev/r/WFBGDkRS8 "Build a retrieval system")[Query the retrieval system](https://api.daily.dev/r/WFBGDkRS8 "Query the retrieval system")[Improve results with Cohere Rerank](https://api.daily.dev/r/WFBGDkRS8 "Improve results with Cohere Rerank")[Conclusion](https://api.daily.dev/r/WFBGDkRS8 "Conclusion") 14 Impressions Comment Bookmark Copy Share your thoughtsPost [](https://daily.dev/sources/aws) [AWS](https://daily.dev/sources/aws "https://daily.dev/sources/aws") AWS' platform is a leading cloud computing platform, offering insights into cloud infrastructure, se... 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