How Clarus Care uses Amazon Bedrock to deliver conversational contact center interactions

Favorite This post was cowritten by Rishi Srivastava and Scott Reynolds from Clarus Care. Many healthcare practices today struggle with managing high volumes of patient calls efficiently. From appointment scheduling and prescription refills to billing inquiries and urgent medical concerns, practices face the challenge of providing timely responses while maintaining

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Shared by AWS Machine Learning February 3, 2026

Scale AI in South Africa using Amazon Bedrock global cross-Region inference with Anthropic Claude 4.5 models

Favorite Building AI applications with Amazon Bedrock presents throughput challenges impacting the scalability of your applications. Global cross-Region inference in the af-south-1 AWS Region changes that. You can now invoke models from the Cape Town Region while Amazon Bedrock automatically routes requests to Regions with available capacity. Your applications get consistent response

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Shared by AWS Machine Learning January 31, 2026

Simplify ModelOps with Amazon SageMaker AI Projects using Amazon S3-based templates

Favorite Managing ModelOps workflows can be complex and time-consuming. If you’ve struggled with setting up project templates for your data science team, you know that the previous approach using AWS Service Catalog required configuring portfolios, products, and managing complex permissions—adding significant administrative overhead before your team could start building machine

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Shared by AWS Machine Learning January 31, 2026

Scaling content review operations with multi-agent workflow

Favorite Enterprises are managing ever-growing volumes of content, ranging from product catalogs and support articles to knowledge bases and technical documentation. Ensuring this information remains accurate, relevant, and aligned with the latest business facts is a formidable challenge. Manual content review processes are often slow, costly, and unable to keep

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Shared by AWS Machine Learning January 30, 2026

Build an intelligent contract management solution with Amazon Quick Suite and Bedrock AgentCore

Favorite Organizations managing hundreds of contracts annually face significant inefficiencies, with fragmented systems and complex workflows that require teams to spend hours on contract review cycles. This solution addresses these challenges through multi-agent collaboration—specialized AI agents that can work simultaneously on different aspects of contract analysis, reducing cycle times while

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Shared by AWS Machine Learning January 28, 2026

Build reliable Agentic AI solution with Amazon Bedrock: Learn from Pushpay’s journey on GenAI evaluation

Favorite This post was co-written with Saurabh Gupta and Todd Colby from Pushpay. Pushpay is a market-leading digital giving and engagement platform designed to help churches and faith-based organizations drive community engagement, manage donations, and strengthen generosity fundraising processes efficiently. Pushpay’s church management system provides church administrators and ministry leaders with insight-driven

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Shared by AWS Machine Learning January 28, 2026

How the Amazon.com Catalog Team built self-learning generative AI at scale with Amazon Bedrock

Favorite The Amazon.com Catalog is the foundation of every customer’s shopping experience—the definitive source of product information with attributes that power search, recommendations, and discovery. When a seller lists a new product, the catalog system must extract structured attributes—dimensions, materials, compatibility, and technical specifications—while generating content such as titles that

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Shared by AWS Machine Learning January 24, 2026