ClusterPower AI as a service

AI is powering change in every industry across the globe. We create custom made, scalable solutions, using our state-of-the-art NVIDIA AI infrastructure. Our powerful setup ensures high speed of deployment, from proof of concept to fully implemented, operational solutions.

Focus on science and increase productivity by leveraging our AI Infrastructure and Platform as a service technology.

Benefit of an AI purpose-build infrastructure (hardware and middleware) – a turnkey solution for all types of AI workloads in one place.

Combine the latest and most powerful hardware technology, dedicated & tested architecture and the DEV-OPS tools required to get the job done faster and at optimized costs.

Gain competitive advantage through deployments of machine learning tools and technologies.

AI – Infrastructure as a Service

Cluster Power AI Infrastructure is based on the NetApp ONTAP AI integrated solution powered by NVIDIA DGX^™ systems and NetApp cloud-connected, all-flash storage.

At the heart of ONTAP AI is the DGX A100 system, a universal building block for data center AI that supports DL training, inference, data science, and other high-performance workloads from a single platform, for every AI workload.

DGX A100 offers the unprecedented ability to deliver fine-grained allocation of computing power, using the Multi-Instance GPU (MIG) capability in the NVIDIA A100 Tensor Core GPU, which enables administrators to assign resources that are right-sized for specific workloads.

NetApp AFF systems keep data flowing to DL processes with the industry’s fastest and most flexible all-flash storage, which features the world’s first end-to-end NVMe technologies. The AFF A800 can feed data to DGX systems up to 4 times faster than competing solutions do.

AI – Platform as a Service

An out of the box platform as a service for AI that spins up a full-fledged ML development environment with all the tools you need at your fingertips.

Streamline data management by connecting all the necessary data sources (cloud or on-premises) and having data pipelines for automatic extraction or batch fetching in a suitable format set up for you. When configuring your ML environment, all incoming data gets automatically validated against the set parameters, and then transferred to a centralized repository.

We offer access ready-to-use feature sets for model training, re-training, and validation.

Optimize Infrastructure Management with our custom-built platform which provides complete visibility into models’ GPU/CPU usage across and nodes and clusters. That way, our customers can continuously optimize job scheduling and resource allocation.

We also keep the data-hungry models at bay, while ensuring that other ML pipelines get access to the right amount of storage they need at the optimal speed.

Constraint-free deployment – Rely on containers or serve your models as API services using the framework you prefer — Flask, Spring, or TensorFlow.js.

Ready to Power your Business?

The power is in your hands