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• Greater agility, flexibility and control • Cost reduction and process innovation • Improved user experience on a range of workstations and devices
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Deliver a global, agile, high-performance application delivery platform that improves service delivery and productivity.
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Hyundai AutoEver, a key player in supporting Hyundai Motor Group’s IT initiatives, faced challenges in developing the connected car of the future. With over four million Hyundai vehicles connected to the cloud, a number expected to increase annually, the company aimed to provide personalized digital experiences for drivers. However, to achieve this, Hyundai AutoEver had to modernize their applications and technology. A prime example of this was their Bluelink® mobile app, a luxurious, connected car service offering various features such as remote start, door lock and unlock, on-demand diagnostics and alerts, destination search, and remote car finder.
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Thales Digital Identity and Security (DIS) is a multifaceted enterprise, providing IT and security services for IoT government programs, banking, mobile encryption, and biometrics. The company began its journey to the cloud after recognizing the benefits of Amazon Web Services (AWS), which allows flexibility of the public cloud in terms of costs and diversity of services. The team quickly moved a dozen legacy solutions to AWS by lifting and shifting, the main objective being to keep customers happy while respecting the service-level agreement. However, after implementing AWS, Thales DIS found it was difficult to control cloud costs. The cloud providers’ native tools they were using were not able to answer all of their needs. The team soon recognized the need for a comprehensive cloud management platform to attain visibility into the growing cloud environment and to implement cost optimization practices.
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neurothink, a US-based start-up, aimed to make machine learning (ML) and artificial intelligence (AI) 'radically accessible' to a broad audience, including data scientists, enterprises, students, and hobbyists. However, the barriers to entry into ML were high due to fragmented platforms, scarce access to powerful GPUs, and a steep learning curve for creating and training models. Additionally, neurothink faced the challenge of delivering a robust, enterprise-capable platform built on start-up resources. They needed an automated, efficient platform that could deliver huge amounts of compute power in a secure environment. The company also needed to ensure a quick market entry to seize the first-mover advantage, which required a superior product and the right partnerships.
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Techedge, a company that aids organizations in accelerating their digital transformation, was facing a challenge with its Kubernetes-based services and solutions. The use of public cloud platforms, while initially beneficial, was proving to be costly and barely scalable when operating on a large scale. As their new line of business began to grow, it became necessary to move from the public cloud to a larger platform with more containers. This new platform required special customization, not just for the apps but also for the container-based model in general, in terms of both security and optimization settings, and customer preferences. This level of customization was not possible in the public cloud.
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