Benefits
-
Infrastructure Agnostic
Deploy in any environment—on-premises, in a private cloud, across multiple public clouds, or in a hybrid setup. Provides organizations unparalleled flexibility to choose the best environment for their specific needs.
-
Vendor Independence
Avoid vendor lock-in by running the platform on any infrastructure. This allows you to leverage the strengths of different providers or your own data center.
-
Open-Source Leverage
Utilize open-source frameworks and tools, which can reduce costs and increase flexibility compared to proprietary cloud-based services.
-
Hassle-Free Setup
Users can get started quickly with pre-configured environments in minutes. Automated updates and maintenance ensure that the latest features and security patches are always available without manual intervention.
-
Expert Support
24/7/26 access to a world class team of experts. Ensure your ML operations run smoothly and efficiently. Reduce the need for dedicated IT staff to maintain and troubleshoot infrastructure, allowing teams to focus on innovation and development.
-
Cost-Effective
Optimize your resources and reduce overhead allowing you to invest more in research and development. Avoid the potentially unpredictable costs associated with cloud usage. Optimize resource allocation according to your specific needs. Tailor the hardware and software stack to meet your specific machine learning workloads, leveraging specialized hardware like GPUs as needed.
-
Consistent Experience
Provide your users with a unified, consistent interface regardless of the underlying infrastructure, simplifying training, development, and operational processes.
-
Operational Control
Full Operational Control to manage, monitor, and secure the environment according to your organization’s policies. This includes control over updates, patches, and system configurations and integration with existing DevOps, CI/CD pipelines, and monitoring tools to create a unified and standardized practice.