On-premise generative AI

Your models, on your GPUs.

Large Language Models and computer vision installed in your company: high-performance serving with NVIDIA Triton Inference Server, data that never leaves your network, predictable costs. The path for those whose documents, drawings or images cannot end up on a third-party cloud.

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In practice

Sizing

We choose hardware and models based on real workloads: number of users, context length, expected latency, energy budget. No oversized GPUs.

Serving with Triton

NVIDIA Triton Inference Server and TensorRT(-LLM) to serve multiple models in parallel — LLM, vision, embeddings — with dynamic batching, versioning and metrics.

Open-weight models

Selection, quantization and fine-tuning of open-weight models on company data, with reproducible evaluations before release.

Air-gap and governance

It also works fully isolated from the internet. Logs, access control, AI system registry and documentation ready for the EU AI Act.

Stack and technologies

NVIDIA Triton · TensorRT
PyTorch
Hugging Face
ONNX
Docker
HPE

Project

Delivered

On-premise LLMs and computer vision for a local company

An HPE system with four NVIDIA Tesla GPUs installed on site to keep privacy at its maximum: language models to query internal documentation and vision models on processes, served with NVIDIA Triton. No data leaves the company.

Hardware: HPE · 4× NVIDIA Tesla GPUs
Models: LLM + computer vision
Serving: NVIDIA Triton Inference Server
Data: 100% on-premise

How we work

Four steps, always the same

01
Assessment of workloads and privacy constraints
02
Model and hardware selection, cost estimate
03
Installation, Triton serving, integration (RAG, APIs, SSO)
04
Acceptance with metrics, training, continuous monitoring

Frequently asked questions

How does it compare to cloud costs?

It depends on volumes: above a certain usage threshold on-premise costs less than pay-per-token and removes the risk of data leaving the premises. We estimate it in the first assessment with your real numbers.

Which models can you install?

Open-weight models for language, vision and embeddings, quantized and optimized for your GPUs; fine-tuned on your data when needed.

Is an internet connection required?

No: the system can run fully isolated (air-gapped). Model updates are planned and applied in controlled windows.

Related capabilities

All AI capabilities →

RAG & LLM

RAG and LLMs on company data

Answers with sources, from your documents: invoices, manuals, contracts — locally too.

Computer Vision

Industrial Computer Vision

Cameras that check quality and safety in real time, on the line or on-premise.

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