GE Healthcare uses Amazon SageMaker to build machine-learning models that help healthcare providers identify health issues faced by people around the world. The company runs its GE Health Cloud—which connects to 500,000 imaging devices—on AWS and uses Amazon SageMaker to ingest de-identified data, store that data compliantly, orchestrate work across teams, and build deep-learning algorithms to identify critical health conditions.
Peloton relies on AWS to power its on-demand, live leaderboard. Learn More>>
Cerner chose AWS to power its machine learning and artificial intelligence. Learn More>>
Expedia is all in on AWS, with plans to migrate 80 percent of its mission-critical apps. Learn more »
Atlassian uses AWS to scale its issue-tracking software applications and enhance its disaster recovery and availability. Learn more »
Discover what customers are doing with AWS today
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SimScale Case Study
By providing instant access to computational fluid dynamics and finite element analysis, SimScale has revolutionized high-fidelity simulation technology from a complex and cost-prohibitive desktop application to a user-friendly cloud-based platform accessible to designers and engineers across the world. Watch how the company behind the world’s first production-ready SaaS application for engineering simulation used Amazon EC2 P3 instances to introduce a new simulation method for large-scale CAD models and why it migrated its entire infrastructure to AWS.
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Munich Leukemia Lab Case Study
Munich Leukemia Lab (MLL) is a diagnostics and research institution whose mission is to find a cure for leukemia and lymphoma. MLL uses state-of-the-art molecular and IT-supported methods to shape the future of hematological diagnostics and therapy. Using AWS, MLL reduced the turnaround time to process patient genome data from 20 hours to 3 hours, helping accelerate research and improve diagnosis of leukemia.
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ReAmp Case Study
Reamp, a digital marketing optimization agency, continuously seeks ways to reduce its operating costs to stay competitive. Using Amazon EC2 A1 instances, Reamp reduced operating costs, which allowed the company to lower customer costs, attract more customers, and provide faster service.
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Siemens Translate Case Study
Siemens surveys employees quarterly using AWS machine learning technologies to translate and analyze results in less than two weeks. Siemens provides solutions for power generation and transmission, medical imaging, laboratory diagnostics, and industrial infrastructure and drive systems. The company’s survey-processing solution uses Amazon Translate, a neural machine translation service; Amazon SageMaker, a managed machine learning service; and Amazon Comprehend, a natural language processing service that finds relationships in text.
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Public Good Case Study
Public Good Software used AWS AppSync to reduce latency of its Impact Unit widget by reducing API calls. Public Good Software is a cause-marketing platform that encourages public engagement around social causes. With AWS AppSync, the company easily accesses only the data it needs, improving customer experience through reduced latency and faster time-to-market.
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Delivery Hero Case Study
Delivery Hero saves 70 percent on infrastructure for containerized Kubernetes workloads. The food delivery company transports 1 million food orders a week in 39 countries. Delivery Hero transitioned its Kubernetes clusters to run only on Amazon EC2 Spot Instances to take advantage of unused Amazon EC2 capacity at a discount.
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LA County Case Study
The Los Angeles County Internal Services Department serves county employees and residents via its contact center. With Amazon Connect, a cloud-based contact center, the county offers self-service options to callers, captures sentiment analysis to improve customer service, and provides better working conditions to call agents.
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Amazon F3 Case Study
Amazon F3, the business unit behind Prime Now and Amazon Fresh, shifted both offerings onto one product selection management system built on native AWS tools. Amazon F3 delivers fresh food to customers in as soon as one hour in a growing number of international locations. The new solution uses Amazon RDS to centralize and store data, AWS Lambda and AWS Step Functions for serverless orchestration and business logic implementation, and Amazon API Gateway to validate user tokens.
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