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Building production-ready AI agents requires careful planning and execution across the entire development lifecycle. The difference between a prototype that impresses in a demo and an agent that delivers value in production is achieved through disciplined engineering practices, robust architecture, and continuous improvement. This post explores nine essential best practices for building enterprise AI agents …

AI agents in enterprises: Best practices with Amazon Bedrock AgentCore Read More »

Performing research and clinical analytics on vast amounts of clinical data can be difficult. Healthcare data scientists and epidemiologists possess deep domain expertise in patient care, disease patterns, and clinical outcomes, yet they often spend weeks navigating complex data infrastructures, writing boilerplate code, and wrestling with technical barriers before they can answer a single clinical …

Agentic AI for healthcare data analysis with Amazon SageMaker Data Agent Read More »

Scientists are working to sequence the genome of every known species on Earth. ​ 

We’re expanding Game Arena with Poker and Werewolf, while Gemini 3 Pro and Flash top our chess leaderboard. ​ 

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 quality patient care. Traditional phone systems …

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

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 learning (ML) pipelines. Amazon SageMaker AI …

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

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 times, your users get reliable experiences, …

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

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 pace with dynamic business needs. According …

Scaling content review operations with multi-agent workflow Read More »

Google AI Ultra subscribers in the U.S. can now try out Project Genie. ​ 

We’re launching Google AI Plus in 35 new countries and territories including the US, making it available everywhere Google AI plans are available. ​