Run AI in production, not as an experiment – with scalable GPU infrastructure

Production AI is used not only to develop models but to run them permanently in applications and business processes: generative AI for text, code, images or designs, AI-supported automation of business processes and code generation. Many software companies integrate AI functions directly into their products, for instance intelligent search, automated document processing or recommendation systems. For in-house access to your own knowledge, knowledge management with AI is the right use case. Chatbots, assistance systems and AI-supported analytics platforms are also among the most common production applications.

Production AI applications process large data volumes and complex model structures. GPUs execute many calculations in parallel and are therefore far more efficient than CPU systems – especially when training neural networks and for the inference of generative models. The infrastructure and GPUs at centron are designed not only to train AI models but to run them permanently in production environments.

By default in our own data centre in Germany, on request in Switzerland. Companies benefit from low latency, stable performance and a cloud that is C5-attested and meets the requirements of the GDPR.

Yes. You manage your AI infrastructure yourself or use managed servers from centron: centron then takes over monitoring, operation and optimisation while your team focuses on models, data and applications.

Yes: virtual machines for maximum flexibility and scalability, cloud GPUs for training and inference, managed servers if you want to hand over technical operations entirely. You choose – we take care of the rest.

The choice depends on model complexity, dataset size and required throughput. For smaller projects, especially video and image processing, the RTX A4000 is often sufficient and particularly efficient. The RTX 6000 offers strong performance for more complex workloads; for demanding deep learning models, large batch sizes or intensive training, the NVIDIA A100 is suitable. The RTX 6000 Ada delivers the most computing power and highest efficiency. centron supports you in selecting the optimal GPU type with clear performance profiles and flexibly scalable cloud GPUs.