
AI Workstation products


2U GPU-Server/Workstation inkl. 2x NVIDIA RTX PRO 6000 Blackwell Max-Q WS
SYS-2115HV-TNRT
1x Dedicated IPMI Management

inkl. 1x NVIDIA RTX 5090
devCube-5090
1x 1GbE RJ-45 (IPMI dedicated)

inkl. 1x NVIDIA RTX PRO 6000 WS
devCube-PRO6000WS
1x 1GbE RJ-45 (IPMI dedicated)

inkl. 2x NVIDIA RTX PRO 6000 Max-Q
devCube-PRO-6000-Max-Q
1x 1GbE RJ-45 (IPMI dedicated)

inkl. 2x NVIDIA RTX PRO 5000
devCube-PRO-5000
1x 1GbE RJ-45 (IPMI dedicated)

inkl. 2x NVIDIA RTX PRO 4500
devCube-PRO-4500
1x 1GbE RJ-45 (IPMI dedicated)

inkl. 2x NVIDIA RTX PRO 4000
devCube-PRO-4000
1x 1GbE RJ-45 (IPMI dedicated)

inkl. 2x NVIDIA RTX 6000 Ada
devCube-6000-Ada-R2
1x 1GbE RJ-45 (IPMI dedicated)

inkl. 2x NVIDIA RTX 5000 Ada
devCube-5000-Ada-R2
1x 1GbE RJ-45 (IPMI dedicated)

inkl. 4x NVIDIA RTX PRO 6000 Max-Q
devCube-PRO-6000-MaxQ
1x 1GbE RJ-45 (IPMI dedicated)
What's inside Pre-installed software for AI development

Our AI training workstations are equipped with the latest and most powerful software solutions to optimise your deep learning and AI training:
- Caffe: A fast and efficient deep learning library that is particularly suitable for Convolutional Neural Networks (CNNs).
- Torch: A framework that supports dynamic networks and a simple programming language and is ideal for machine learning and deep learning.
- Theano: A Python library that simplifies the definition, optimisation and evaluation of mathematical expressions with multi-dimensional arrays.
- TensorFlow: An open-source framework specifically designed for training and inference of deep neural networks.
- CUDA (including cuDNN): A parallel computing platform and API from NVIDIA that utilises the power of GPUs to perform intensive computing tasks. cuDNN is a GPU-accelerated library specifically optimised for deep learning.
WHY AI? AREAS OF APPLICATION OF AI TRAINING WORKSTATIONS
Optimise business processes
AI training workstations help to automate business processes through machine learning and make them more efficient. They enable data-driven decisions that reduce costs and increase productivity.
Research and development
In research, AI training workstations analyse large amounts of data quickly and precisely. This supports innovations in areas such as medical diagnostics and pharmaceuticals.
Security and monitoring
Security companies use AI training workstations to improve monitoring systems. AI can recognise threats in real time and suggest preventive measures.
Personalise the customer experience
Companies use AI to analyse customer behaviour and develop tailored marketing strategies. This increases customer satisfaction and loyalty.
Healthcare
In the healthcare sector, AI training workstations support the diagnosis and treatment of diseases. AI models analyse medical data to create precise diagnoses and personalised treatment plans.
Data protection
AI Training Workstations are ideal for data protection, as the data is processed locally and not sent to the cloud. This minimises security risks and ensures the confidentiality of sensitive information.
Would you like to find out more?
Do you need more? Matching hardware for AI training
Our high-performance storage solutions offer high capacity and speed to efficiently store and retrieve large amounts of data. Perfect for the requirements of big data and machine learning.
Our AI training servers are designed for maximum computing power and flexibility. They enable efficient training of complex AI models and are ideal for research and development.
Our inference hardware offers the necessary computing capacity to execute AI models in real time. Ideal for applications such as autonomous vehicles, image processing and voice control.
- What is the difference between an AI Training Workstation and a conventional PC?
AI training workstations are specially designed for the requirements of machine learning and artificial intelligence. They have more powerful processors, more RAM and higher-quality graphics cards in order to process large amounts of data faster.
- Why are powerful GPUs important for AI training workstations?
GPUs (Graphics Processing Units) are crucial for the training of AI models, as they enable the parallel processing of large amounts of data. This speeds up the training process considerably compared to conventional CPUs.
- Can I use an AI Training Workstation for purposes other than AI training?
Yes, AI Training Workstations are versatile and can be used for a variety of computationally intensive tasks, including video editing, 3D modelling and simulations.
- How do I choose the right AI Training Workstation for my project?
The choice depends on the specific requirements of your project, including the type of models to be trained, the size of your data sets and your budget. A consultation can help you find the ideal configuration based on your needs.
- What kind of support do you offer for AI Training Workstations?
Support can range from technical assistance and troubleshooting to regular updates and maintenance services.