AI Infrastructure Services
GPU servers and Kubernetes clusters for AI training and inference, set up on-premises or in your cloud and handed over ready to run.
About our AI infrastructure services
AI projects often stall on infrastructure, not on models. GPUs sit idle. Drivers break after an update. Two teams fight over the same card. Our AI infrastructure services fix that. We design and build GPU servers and GPU clusters for training and inference, in your data centre or your cloud account. Your data scientists get a platform that simply works.
What's included in our AI infrastructure services
How we deliver AI infrastructure services
We start with your workloads. What will you train? What will you serve? How fast must it answer? From there we size the platform and choose on-premises, cloud or hybrid. Everything is built as code with Ansible and Terraform, so it is repeatable and easy to grow. We test it with real jobs before handover. Then we document it, and we can run it for you afterwards.
Tools and technology for AI infrastructure services
Outcomes of our AI infrastructure services
- GPUs shared fairly and kept busy, not idle
- A platform your team can rebuild and scale from code
- One team accountable for hardware, cluster and support
Frequently asked questions about AI infrastructure services
Should we run AI workloads on-premises or in the cloud?
It depends on how steady your usage is. Cloud GPUs are quick to start and good for short bursts. Your own GPU servers usually cost less when they are busy most of the day, and your data stays in your building. Many teams use both. We compare the options for your workload before you buy anything.
Can several teams share the same GPUs?
Yes. On Kubernetes we set up GPU sharing and job queues. Each team gets fair access, and expensive cards are not left idle.
Do you manage the platform after setup?
Yes. We can hand it over to your team with full documentation. Or we can run it for you, with monitoring, patching and support, as part of our managed services.
Related Services
AI & GPU Monitoring Services
Monitoring for GPU clusters and AI applications: GPU health and usage, model latency, errors, token use and cost, in one place.
MLOps & LLMOps Services
Pipelines that take models from experiment to production and keep them healthy: versioning, automated deployment, rollback and drift checks.
Private LLM Deployment
Open-source large language models hosted in your own data centre or cloud account, with document search (RAG) so answers come from your data.
Calculate Your ROI
See the immediate financial impact of moving to Nixsoft's automated open-source solutions.
ROI & TCO Calculator
See how much you save with Open-Source Automation
Based on an average 40% reduction in cloud waste and automated maintenance overhead.
Solving Complex Engineering Challenges?
Let's build a roadmap tailored to your specific infrastructure needs.
Talk to an Architect