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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AWS Case Study - Perfect Corp.
Building its AI- and AR-enabled beauty platform on AWS has allowed Perfect Corp. to scale its business to 67 countries in three years and exceed its 99.58% service availability target. Perfect Corp. is a beauty SaaS vendor in Taiwan offering a platform for global beauty businesses and customers that allows them to virtually try on makeup online, in-store, or through a mobile app. The company is using Amazon EMR to process big data and analyze logs, Amazon RDS to store customer data, and Amazon GuardDuty to monitor for security threats.
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Orsted/Obviux Case Study
Green energy company Ørsted created its own software startup, Obviux, built entirely in the cloud. Obviux builds streamlined billing software for the energy sector. The company relies on Amazon RDS for MySQL to manage the Amazon Aurora database it uses to store data from more than 1 million customers and 1.2 million smart meters.
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RADICA Case Study
RADICA can launch campaigns much faster for global brands targeting Chinese consumers now that its multichannel electronic direct-mail platform RiMANGGIS is running on AWS. Headquartered in Hong Kong, RADICA provides digital marketing solutions to around 300 businesses. RADICA’s RiMANGGIS platform manages large-scale email, mobile, and social media activities targeting consumers in China and uses AWS services such as Amazon EC2, Amazon S3, Amazon SQS, and Amazon Route 53, is now more agile and simple to manage.
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Numerate Case Study
Numerate uses AWS to model tens of billions of molecules, discover drug candidates five times faster, and reduce costs by seven-eighths. The organization uses AI and ML technologies to transform drug discovery by running its ML platform on AWS and using Amazon EC2 Spot Instances to drive down costs.
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AWS Case Study - BiiLabs
Using AWS Marketplace, BiiLabs has reduced sales overheads for its blockchain Alfred API service by 50 percent. BiiLabs creates trusted network infrastructures using blockchain and distributed ledger technology. The company uses Amazon EC2 and AMI to run the Alfred API with AWS API Gateway and AWS IAM to manage access.
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Al Tayer Group Case Study
Al Tayer Group relies on AWS to scale to meet 50 percent web traffic growth, reduce operational costs by 79 percent, and focus on development instead of infrastructure management. The organization is a privately held holding company with operations in six countries in the Middle East. Al Tayer Group runs four e-commerce websites and a website platform on AWS, taking advantage of Amazon EC2 Spot Instances to reduce costs.
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Skyscanner Case Study - AWS Support
AWS Support helps Skyscanner to ensure it has the right balance for its for its large volume of EC2 instances (reserved, on-demand, and spot) to make sure its business is optimized for both performance and cost.
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Third Rock Ventures Case Study
Machine learning is increasingly used to support therapeutic discovery at biotech companies. Third Rock Ventures is a venture firm that builds and launches biotech companies that accelerate scientific discoveries and transform patient lives. Dozens of Third Rock portfolio companies make use of AWS services to support their infrastructure, data science, bioinformatics, and machine-learning initiatives. Amazon Elastic Compute Cloud (Amazon EC2) along with flexible storage modalities such as Amazon Elastic File System (Amazon EFS) and Amazon Elastic Block Store (Amazon EBS) empower teams to aggregate complex, semi-structured datasets. Amazon SageMaker notebooks provide a cloud solution for reproducible, easy to implement data science workflows. Similarly, Amazon Comprehend Medical makes it easy to structure medical text data, which enables biotech companies to better collaborate with clinical partners and identify opportunities to serve patients
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