Organizations want AI that speaks their business language, but their most valuable training data is often too confidential to send to external infrastructure. GPU On-Demand compresses idea to production into weeks, letting your team fine-tune models on proprietary data using sovereign GPU infrastructure, then deploy the resulting model wherever you choose.
Organizations increasingly want AI models that understand their own business language, operational procedures, internal policies, and customer interactions. Generic language models give broad responses that employees must manually validate, correct, and adapt to the company context.
Fine-tuning on proprietary data could greatly improve relevance, but those datasets often contain confidential information, regulated documents, or sensitive operational knowledge. Compliance and data-sovereignty concerns prevent many organizations from using external, non-sovereign infrastructure for training, leaving them dependent on generic models with limited business value.
GPU On-Demand by LuxProvide gives users direct, time-bound access to high-performance GPU nodes on MeluXina, Luxembourg’s sovereign digital infrastructure, to train, fine-tune, test, or deploy AI models without long-term commitments.
Users reserve GPU capacity on demand, upload their proprietary dataset to a private workspace, select a base model, and run fine-tuning jobs entirely within sovereign infrastructure, monitoring training metrics throughout.
The result is a portable, fine-tuned model asset, along with evaluation results and a reproducible procedure, that can be deployed wherever the organization chooses, with no lock-in to a specific runtime.
Train on Sovereign Infrastructure
Fine-tune models on confidential data within sovereign GPU infrastructure in Luxembourg, keeping sensitive information compliant and under control.
Make AI Speak Your Language
Adapt models to your organization’s terminology, policies, and procedures so answers reflect your business reality.
Access GPUs on Demand
Reserve high-performance NVIDIA A100 nodes for exactly the time you need, with no long-term infrastructure commitment.
Keep Your Model Portable
Produce a reusable model asset you can deploy on MeluXina, through Flinky, or on your own infrastructure, with no runtime lock-in.
Improve Continuously
Reuse a documented, repeatable fine-tuning process to update the model as new data becomes available, with less manual effort over time.
