GPU capacity planning
Choosing between managed services and on-demand, spot or reserved GPU capacity on AWS, Azure, Google Cloud, OVHcloud, Hetzner Cloud, UpCloud and private clouds, sized to your real training and inference load.
AI infrastructure for training and serving models
We design and operate the infrastructure behind your AI workloads (GPU compute, model serving, vector databases and MLOps pipelines), secure, observable and with GPU costs under control.
What we do
Scope of work
Kubernetes platforms for AI
GPU node pools, autoscaling and job scheduling on EKS, AKS or GKE, with Ray or Kubeflow for distributed training and batch inference.
Model serving and LLM endpoints
Low-latency inference with vLLM, NVIDIA Triton or KServe, and private access to Azure OpenAI, Amazon Bedrock or Vertex AI.
Data and retrieval layer
Feature pipelines and vector databases such as pgvector, Qdrant or Azure AI Search, kept in sync with the source data.
MLOps and observability
Experiment tracking, a model registry, automated deployments and monitoring of latency, cost per request and model drift.
Security and governance
Private networking, secrets management, access control to models and data, and audit logs your compliance team can rely on.
Technologies
Typical technologies
We are not tied to any single vendor: we work on public and private clouds and adapt to your environment, licences and team skills. These are the tools we use most often in this area.
Cloud platforms
- AWS
- Microsoft Azure
- Google Cloud
- OVHcloud
- Hetzner Cloud
- UpCloud
- OpenStack
- VMware
- Proxmox VE
Compute and orchestration
- Kubernetes
- NVIDIA GPU Operator
- Ray
- Kubeflow
- Slurm
Model serving
- vLLM
- NVIDIA Triton
- KServe
- Ollama
- Hugging Face
Managed AI services
- Azure OpenAI
- Amazon Bedrock
- Vertex AI
- OVHcloud AI Endpoints
- Mistral AI
MLOps
- MLflow
- Weights & Biases
- DVC
- Argo Workflows
- Terraform
Vector search and retrieval
- pgvector
- Qdrant
- Milvus
- Weaviate
- OpenSearch
Related services
Often combined with this service
- AWS
- Microsoft Azure
- Google Cloud
- OVHcloud
Cloud Development, Deployment, Migration & Maintenance
Cloud-native development, deployment and migration on AWS, Azure, Google Cloud, OVHcloud, Hetzner Cloud, UpCloud and private clouds, followed by maintenance and post-migration cost and performance optimisation.
- AWS
- Microsoft Azure
- Google Cloud
- OVHcloud
Cloud Cost Optimisation
FinOps practices, rightsizing and commitment planning that cut AWS, Azure and Google Cloud bills without hurting performance.
- AWS
- Microsoft Azure
- Google Cloud
- OVHcloud
Cloud Maintenance & Operations
Managed operations of your cloud environments: 24/7 monitoring, patching, backups, upgrades and incident response.
Let's talk about your project
Tell us where you are today and what you want to achieve. We will suggest a concrete first step, and we can sign an NDA before any technical discussion.