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How Cara pioneers domain-specific AI for enterprise insurance brokerages with AWS

How Cara pioneers domain-specific AI for enterprise insurance brokerages with AWS

Insurance is an $8 trillion global industry burdened by manual workflows and a growing talent shortage. Cara delivers an AI-native solution on AWS that automates back-office processes for insurance brokerages. Insurance agents routinely spend hours on repetitive tasks. These include completing applications, analyzing policy coverages, re-keying data across systems, and relaying information between clients and […]

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Production-grade AI agents for financial compliance: Lessons from Stripe

Production-grade AI agents for financial compliance: Lessons from Stripe

This post is co-written by Christopher Phillippi and Chrissie Cui from Stripe. Stripe processes $1.4 trillion in annual payment volume across 50 countries, requiring compliance teams to review thousands of transactions daily. This post explores how Stripe built a production-grade AI agent system on AWS using Amazon Bedrock that reduced review handling time by 26

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Retrofit, don’t rebuild: Agentic overlays for transforming legacy enterprise services

Retrofit, don’t rebuild: Agentic overlays for transforming legacy enterprise services

The opinions expressed in this post are the authors’ views and not those of Cisco. Enterprise architectures have long been centered on REST APIs and microservices. These systems are stable, well-tested, and deeply embedded in production environments. They weren’t designed for Agent-to-Agent (A2A) communication, the emerging standard for autonomous agents that collaborate, reason, and coordinate

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Optimize model training on Amazon SageMaker AI with NVIDIA Blackwell

Optimize model training on Amazon SageMaker AI with NVIDIA Blackwell

Optimizing model training on Amazon SageMaker AI with NVIDIA Blackwell GPUs changes what’s practical for large AI models. If you train large models today, you are likely working around a familiar set of constraints: batch sizes limited by GPU memory, sequence lengths cut short to avoid out-of-memory errors, and model sharding that adds communication overhead

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Implementing super resolution by deploying SeedVR2 on Amazon SageMaker AI

Implementing super resolution by deploying SeedVR2 on Amazon SageMaker AI

As display technologies advance to higher resolutions, many organizations face a common challenge: their existing video libraries contain lower-resolution content that appears pixelated or blurry on modern high-definition displays. Traditional video upscaling approaches often struggle with computational limits, inconsistent quality, and scalability issues when processing large video collections. Many existing solutions also lack the techniques

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Build self-service AWS Health analytics to find actionable health insights with AI agents powered by Amazon Bedrock

Build self-service AWS Health analytics to find actionable health insights with AI agents powered by Amazon Bedrock

On a typical Monday morning, an enterprise operations team receives multiple AWS Health notifications about Amazon Linux 2 end-of-life, RDS version deprecations, and EC2 instance retirements across 50+ accounts. Without self-service analytics, the team has no way to quickly identify the events that affect production systems, the events that require immediate action versus long-term planning,

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Building agentic AI applications with a modern data mesh strategy on AWS

Building agentic AI applications with a modern data mesh strategy on AWS

When a customer service agent autonomously queries order databases, retrieves return policies, and synthesizes answers, it needs governed access to multiple data sources across your organization. Building agentic AI applications on a modern data mesh requires fine-grained access control enforced at every layer of the data interaction chain. AI agents that autonomously discover database schemas,

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Huntington Bank: Redacting sensitive data from 400M+ documents with AWS

Huntington Bank: Redacting sensitive data from 400M+ documents with AWS

When your document repository contains hundreds of millions of files accumulated over nearly a decade, how do you systematically find and redact sensitive customer data without taking years to complete? This was the challenge facing The Huntington National Bank (Huntington), a top 10 bank in the United States. Redacting sensitive information at scale Since 2015,

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Build a healthcare appointment agent with Amazon Nova 2 Sonic

Build a healthcare appointment agent with Amazon Nova 2 Sonic

If you run a clinic or hospital network, you already know the cost of missed appointments. The average no-show rate across US healthcare sits between 5–30 percent, depending on specialty. Each empty slot represents lost revenue, idle provider time, and delayed patient care. The standard fix, calling patients one by one to confirm or reschedule,

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