Services

Custom models on your data.

From data preparation and fine-tuning to evaluation, MLOps and deployment — models trained for your problem.

What model training looks like with us

When an off-the-shelf model won't cut it, we train and fine-tune your own — on your data, for your problem. From data preparation through evaluation to deployment and monitoring, it's engineering, not alchemy.

We build the MLOps around the model too, so retraining, versioning and rollback are routine rather than heroic.

  • Data preparation
  • Training & fine-tuning
  • Evaluation
  • MLOps
  • Deployment
  • Monitoring & drift
train.py
for epoch in range(epochs):
for x, y in loader:
optimizer.zero_grad()
loss = criterion(model(x), y)
loss.backward()
optimizer.step()
evaluate(model, val_loader)
Technology

The stack behind it

  • PyTorch
  • TensorFlow
  • Hugging Face
  • MLflow
  • Kubernetes
  • GPU infrastructure
Deliverables

What you walk away with

A trained, evaluated model
A reproducible training and data pipeline
Deployment with versioning and rollback
Monitoring for drift and performance
FAQs

Common questions

  • It depends on scope — most projects start with a short paid discovery so you get a firm estimate before committing. Book a call and we'll give you a realistic range.
  • Small projects ship in weeks; larger platforms over several months. We work in short increments so you see progress from the start.
  • Yes, we sign NDAs, and you own all the IP and code we produce for you. That's non-negotiable on our side.
  • Data protection is built into how we work — UK GDPR by design, secure-by-design engineering and accessibility to WCAG 2.2 AA. We're working towards ISO 27001 and Cyber Essentials certification, and we're happy to complete your security questionnaires.
Ready when you are

Let's build something that lasts.

Book a free 30-minute call with a senior engineer. No sales pitch — just an honest view on whether we're a fit.