[ Engineering ]
Infrastructure
& AI Deployment
We design and operate the infrastructure that runs your models in production — sovereign, scalable, and observable. From first deployment to full industrialization of your AI systems.
[ Offerings ]
Three deployment models
On-Premise Deployment
Deploy LLMs and agents on your own servers with full data sovereignty. No cloud dependency, no shared tenants — your AI runs entirely within your controlled perimeter.
Bare Metal Deployment
Maximum performance on dedicated hardware with no shared tenant risk. Direct access to GPU compute with optimized inference stacks for latency-critical workloads.
Custom Cloud Setup
Private cloud configurations on certified sovereign infrastructure. Scalable, compliant, and fully managed — built around your security and regulatory requirements.
[ Tech Stack ]
Infrastructure built for AI production
We use proven tools — Kubernetes, vLLM, Triton Inference Server, Ray — adapted to your latency and volume constraints. Every deployment includes a full observability layer (Prometheus, Grafana, distributed traces), robust data pipelines, and an architecture ready for scale.
[ Unfair advantages ]
What your teams concretely gain
Sovereign Hosting
100% French territory infrastructure — data, models, and logs never leave your perimeter.
Seamless Integration
APIs compatible with your existing tools: no overhaul, no forced migration, progressive deployment.
MLOps & Observability
Real-time monitoring, drift alerts, automatic rollback, and dedicated performance dashboards.
[ Implementation ]
Custom design and field support
Step 1
Existing Architecture Audit
Mapping your current stack, identifying constraints, and defining the infrastructure target.
Step 2
Environment Setup
Server provisioning, CI/CD pipeline configuration, network security, and secrets management.
Step 3
Deployment & Continuous Monitoring
Progressive deployment with canary releases, full observability, and guaranteed SLA.
[ Next Step ]