Scalable and Performant Kubernetes for AI & Machine Learning

Maximize computational power without the complexity. Fast, efficient, and built for demanding workloads.

Machine learning workloads require scalable infrastructure to handle intensive processing and data needs. With Syself, you get a powerful, production-ready Kubernetes environment that adapts to your workloads—at a fraction of the cost of other solutions.

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Cost reduction: 80%
Faster time to market: 65%
Reduction in outages: 38%
Faster request times: 90%

Power Innovation, Not Infrastructure

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Optimized Cost Control

Cut down on infrastructure costs without compromising on performance. By using affordable, high-performance providers like Hetzner, Syself gives you access to powerful compute resources at a fraction of the usual price, making AI projects more affordable.

High Performance

Each Kubernetes cluster is optimized out of the box for the heavy computational loads typical of AI and machine learning workloads. From data processing to model training, you get smooth, uninterrupted performance—so you can focus on innovation, not infrastructure.

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Tailored for AI Workloads

Syself is built with AI and machine learning in mind, offering infrastructure that’s ready to handle intensive computational demands, with GPU support.

Scale Without the Overhead

AI projects often experience rapid scaling requirements, but with Syself, you don’t need a team of Kubernetes experts. Our platform scales with your business, so you can focus on your algorithms while we handle the infrastructure behind the scenes.

Scalable Power at a Fraction of the Cost

AI and machine learning projects can burn through cloud budgets fast, but Syself helps you keep costs in check. By tightly integrating with cost-efficient providers, you get all the computational power you need without paying the sky-high prices of traditional cloud solutions.

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Unlock Unmatched Performance with Bare Metal and GPU Support

Syself treats bare metal servers as first-class citizens, delivering unmatched performance for AI and machine learning workloads. With direct access to hardware, you get lower latency and more control, making it ideal for resource-intensive tasks.

For AI projects requiring heavy computational power, Syself supports GPU-enabled bare metal servers, accelerating tasks like model training and inference. This combination of bare metal and GPU ensures your infrastructure is optimized for speed, performance, and scalability—no virtualization layer in between.

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Syself Powers Kubernetes From Zero to Production With Hesse.ai

Hesse.ai is a German company building a platform that makes studies easier with AI and machine learning. Their goal is to enable students to learn any subject of their choice.

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Improve Your MLOps Practices With These Features

Machine Learning Ready

Get a scalable and flexible infrastructure for machine learning tasks.

Pre-configured Clusters

Use configuration files to define the desired state of your infrastructure and applications.

Gitops Ready

Use Git as the single source of truth for your configurations.

GPU Support

Deploy and manage GPU-accelerated workloads within your Kubernetes clusters.

SLA and Support

Around-the-clock support to ensure your cluster is always running smoothly.

Self-Healing

Automatically detect and fix issues in your infrastructure without human intervention.