MLOps & DevOps

While using an third-party AI provider can be a great choice to prototype new AI use-cases, at some point you may want to switch to a private cloud to run your models and AI workflows. This offers a couple of advantages:

Increased privacy as data never leaves your data center or cloud
Better cost control with dedicated hardware
Assurance that customer data does not accidently leaks into model training

How we can help you

Getting your AI models up and running can be tricky though. While major cloud providers offer state of the art hardware, it often comes at the price of increased complexity. We can support you in every stage of your AI infrastructure endeavour, such as:

Setting up your AI infrastructure on Scaleway, AWS or Azure
Finding the optimal Hardware setup
Development of AI Infrastructure as Code (Terraform, Pulumi, CDK)
Tuning of inference servers like vLLM, Lorax or Triton

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