Category: Amazon Bedrock Agents

Radiology training stands at a crossroads. While imaging volumes surge and diagnostic complexity increases exponentially, the traditional apprenticeship model struggles to deliver comprehensive education without compromising patient care delivery. How can radiology educators deliver thorough and personalized instruction to users without impacting their clinical responsibilities? Also, can such a personalized radiology education be scaled to […]

Digital Product Passports (DPPs) are set to transform the landscape of product transparency, regulatory compliance, and supply chain sustainability—yet organizations face challenges integrating data, verifying information, and adapting to evolving rules. In this post, we explore how we see AWS customers address the topic of DPPs and the role agentic AI plays in automating and […]

Smart product manufacturers are at a critical transformation point. With Gartner predicting that 80% of AI models will be industry-specific by 2027, and their recent analysis showing that AI-enabling cloud services are the future of cloud infrastructure, companies can no longer rely solely on traditional hardware sales to maintain competitive advantage. The shift toward digital […]

The payments industry stands at a transformative inflection point. Traditional payment systems built on rigid rules, manual processes, and legacy infrastructure find it difficult to navigate the evolving landscape of modern commerce. Today’s payment ecosystem demands solutions that handle increasing complexity while delivering the seamless, contactless, and autonomous experiences customers expect. Financial institutions have long […]

In the race to harness the transformative power of generative AI, Healthcare and Life Sciences (HCLS) organizations face a critical challenge: how to innovate rapidly while navigating complex regulatory requirements. Promising generative AI solutions are being developed to revolutionize everything from patient care to drug discovery. However, many organizations find themselves paralyzed at the intersection […]

AI has the potential to transform every supply chain process. While existing technologies such as predictive analytics, Internet of Things (IoT), and machine learning (ML) have improved supply chain efficiency and visibility, organizations still face significant challenges. Today’s supply chain practitioners must navigate complex scenarios ranging from geo-political tensions to natural disasters, while managing data […]

Telecom Network Operations are complex by nature, needing constant vigilance across a range of activities such as real-time alarm monitoring, scheduled maintenance tracking, and performance analytics. One of the most critical metrics in this domain is Mean Time to Resolve (MTTR)—a key indicator of how efficiently network teams can detect, diagnose, and resolve issues. A […]

Large language models (LLMs) and AI agents have revolutionized the orchestration of complex workflows by using their ability to interact with their environment and reason through actions. Agentic AI solutions bring a new level of flexibility and intelligence, unlike traditional machine learning (ML) methods, which often need complete retraining for new tasks and struggle to […]

Water utilities worldwide are facing challenges in managing infrastructure, reducing water waste, and making sure of reliable service delivery. The traditional approaches of manual monitoring and reactive maintenance are no longer sufficient due to increasing water demand, need for uninterrupted service, regulatory requirements, and customer satisfaction. In this post, we explore how Amazon Web Services (AWS) AI […]

In today’s complex industrial environments, predictive maintenance remains a key challenge for Energy, Utilities, and Manufacturing sectors. Traditional anomaly detection methods are labor-intensive and time-consuming, often leaving critical equipment vulnerabilities unaddressed for hours or days—leading to significant unplanned downtime and financial impact. McKinsey estimates mid-size refineries lose $20–50 million annually due to reliability issues. Typical […]