On-premise AI
Private hosting of models, data and inference services. Full control over the perimeter.
En clair : Your data stays under your governance.
In plain terms
The right power — neither over- nor under-sized.
GPU sizing, vector storage and training/inference pipelines, on-prem or cloud. Over-sizing costs; under-sizing kills the user experience.
Routing, quotas, costs, and response quality are managed as a critical service. Multi-model does not mean chaos.
MLOps: versioning, deployment, continuous evaluation, and rollback. A model without a lifecycle is a POC in disguise.
Air-gapped and isolated networks are possible when the context requires it. Architecture starts from constraints, not from a SaaS demo.
GPUCalibrated power
MLOpsLifecycle
CostSteered inference
On-premSovereignty
What we do
Run AI as a critical service.
An execution foundation for models, vectors and MLOps pipelines.
Model orchestration
Routing, quotas, optimization, and multi-model governance.
En clair : The right model for the right use, at the right cost.
AI observability
Traces, costs, performance and response quality.
En clair : We see drift, latency, and cost.
MLOps pipelines
Versioning, deployment and continuous evaluation.
En clair : The model evolves under control.
Vector storage
Indexes, retention and semantic search performance.
En clair : Knowledge is served at the right latency.
Frequently asked questions
AI infrastructure — questions.
Open source or proprietary APIs?
Both: depending on latency, cost, confidentiality, and target accuracy. Often a mix routed intelligently.
Air-gap possible?
Yes — architectures designed for isolated or disconnected networks. The constraint guides the design from day one.
How do you control costs?
Quotas, caching, model routing, batching, and observability of tokens/requests. AI FinOps is an architecture topic.
Kubernetes mandatory?
Common, not mandatory. Bare-metal GPU and dedicated runtimes exist depending on the case.
Link to RAG?
Infra carries the embeddings, indexes and inference services RAG depends on. Both are sized together.
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