At the core of all RxDS solutions is a versatile analytics ecosystem comprised of open-source libraries for machine learning and complex web development frameworks to implement the machine learning capabilities.
The architecture is compatible with both on-premises deployments for sensitive workloads as well as virtual-private cloud enabled implementations in AWS, Azure, Google Cloud and other environments. RxDS also provides container-ised solutions that can b deployed in various operating systems for consistency.
The ML/AI Open-Source Software (OSS) Stack comprises of R, Python, and Julia libraries. Popular ML packages such as scikit-learn, tensorflow, pyTorch (Python), caret, e1071, nnet (in R), JuliaML utilities are pre-configured within the solutions and can be executed in-database.
All solutions are backed by a High-Performance Computing (HPC) architecture stack that comprises of NVMe and GPU based AWS EC2 instances for fast I/O, multi-core parallel processing and deep learning capabilities via GPU integration.
Web-frameworks from the Javascript world, the industry and enterprise standard, power all of RxDS applications. Our full-stack team leverages well-known solutions such as Angular, Ember, React, and node.js to deliver functionality-rich interactive front-ends for end-users to make use of the underlying machine learning capabilities.
All solutions from RxDS include an administrative layer that includes various administrative functionalities such as user management, auditing, and granular table-level access control. Industry-leading security standards are integrated along with a governance layer that includes process management.
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