Germany
Sweden
Luxembourg
Germany
France
Netherlands
Netherlands
France
France
Italy
Ireland
Hyperscalers, EU regions
Julian Teicke
Founder wefox & The Delta
[
CONTINENT COMPUTE CLOUD
]
A platform for training, hosting, and optimizing AI models.
Train, host, continuously improve: on EU infrastructure, with our researchers alongside your team.
[
TRAINING
]
Sovereign infrastructure for faster, better, and more affordable AI models.
Post-training for your task, not for the average.
Distillation, fine-tuning and RL on your data, in your harness and with graders your experts define. The method follows the task, not the other way round.
Optimise for your evals, not for benchmarks.
The eval set is built from your real cases and frozen before the first training run. You calibrate rewards to your product KPIs and see per checkpoint what the model has learned.
Stay flexible on the base model.
Start on the best open model available today and move to the next one as soon as it ships. Eval set, data pipeline and endpoint stay the same, and only what beats the baseline gets rolled out.
[
INFERENCE
]
Flexible, production-grade inference on dedicated GPUs in the EU.
Serve in the environment you trained in.
Checkpoint, tokenizer and prompt format move from training to the endpoint unchanged. What you evaluated is exactly what runs in production.
Sized for your workload, run under EU law.
From asynchronous batch jobs to real-time applications: you set throughput, latency and concurrency per deployment. Dedicated GPUs in EU data centres, no US hyperscaler in the chain.
From checkpoint to endpoint, no detours.
Any checkpoint that passes the eval gate goes straight to your endpoint, with an audit trail for every step. The API is OpenAI-compatible: your applications only swap endpoint and key.
[
OPTIMIZATION
]
Models that get better the more they are used.
Turn real usage into training data.
Traces, corrections and reviewer feedback from the endpoint become examples and reward signals for the next training run. The model learns from the cases you actually see.
Retraining behind a fixed eval gate.
Every new version has to beat the current model on the same eval set, or it does not go live. Version by version, you see what was learned and where gaps remain.
Roll out with A/B tests, monitoring and rollback.
Release candidates run against the current version before they get all the traffic. You see accuracy, cost and latency per version, and you can roll back at any time.
[
COLLABORATION
]
Two ways to work with us, depending on how much you want to keep in your own hands. The infrastructure underneath is the same.
Embedded
We sit with your engineers, from co-designing the first eval, to deploying the model and beyond.
Managed
Your team designs and runs experiments. We manage the training, serving, and infrastructure load.
[
SOVEREIGNTY
]
Built for customers with the highest demands on sovereignty, security and speed.
DSGVO
EU AI ACT
DORA
Data never leaves the EU.
Training and inference run on dedicated GPUs in EU data centres under EU law. No US hyperscaler in the chain, data processing agreement in place before the first record.
Every decision traceable, down to the training run.
Versioned data, evals and checkpoints, audit logs for every step, mapped to the obligations under the EU AI Act and DORA. Documentation is produced in the process, not afterwards.
You own the intelligence.
Weights, eval set and documentation are yours. You decide what gets trained and what gets rolled out, and you can take the model with you at any time, onto your own infrastructure if you wish.