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Generate user-personalized communication with Amazon Personalize and Amazon Bedrock

AWS Machine Learning

Personalized outbound communication can be a powerful tool to increase user engagement and conversion. To achieve this, you can use Amazon Personalize to generate user-personalized recommendations and Amazon Bedrock to generate the text of the email.

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Build generative AI applications quickly with Amazon Bedrock IDE in Amazon SageMaker Unified Studio

AWS Machine Learning

SageMaker Unified Studio setup SageMaker Unified Studio is a browser-based web application where you can use all your data and tools for analytics and AI. This will provision the backend infrastructure and services that the sales analytics application will rely on. You’ll use this file when setting up your function to query sales data.

APIs 107
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Build a video insights and summarization engine using generative AI with Amazon Bedrock

AWS Machine Learning

Furthermore, these notes are usually personal and not stored in a central location, which is a lost opportunity for businesses to learn what does and doesn’t work, as well as how to improve their sales, purchasing, and communication processes. With Lambda integration, we can create a web API with an endpoint to the Lambda function.

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Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning

It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. API Gateway is serverless and hence automatically scales with traffic. API Gateway also provides a WebSocket API. Incoming requests to the gateway go through this point.

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Unlocking insights and enhancing customer service: Intact’s transformative AI journey with AWS

AWS Machine Learning

In this post, we demonstrate how the CQ solution used Amazon Transcribe and other AWS services to improve critical KPIs with AI-powered contact center call auditing and analytics. Additionally, Intact was impressed that Amazon Transcribe could adapt to various post-call analytics use cases across their organization.

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Discover insights from Gmail using the Gmail connector for Amazon Q Business

AWS Machine Learning

We provide the service account with authorization scopes to allow access to the required Gmail APIs. After you create the project, on the navigation menu, choose APIs and Services and Library to view the API Library. On the API Library page, search for and choose Admin SDK API. Choose Enable to enable this API.

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Elevate workforce productivity through seamless personalization in Amazon Q Business

AWS Machine Learning

Personalization can improve the user experience of shopping, entertainment, and news sites by using our past behavior to recommend the products and content that best match our interests. You can also apply personalization to conversational interactions with an AI-powered assistant.