Fine-tuning
Adapt open-source or hosted models to your domain, language, tone and tasks.
Service 04 · AI model training
Models trained on your data, proven before they ship.
When a general-purpose model isn’t enough, we fine-tune or train models on your own data — and prove the improvement with evaluations you can trust.
What we do
Better models, measured honestly.
Training is only worth it when it beats the alternatives. We check that first, then make every improvement measurable.
Data preparation
Collect, clean, label and version the data a model learns from, with clear labelling guidelines.
Evaluation
Benchmarks and test sets built from real cases, compared against a baseline before anything ships.
Classic machine learning
Classification, forecasting and recommendation models where they fit better than a language model.
Private deployment
Run models in your cloud or on your own servers, with monitoring and access control.
Continuous improvement
Retraining pipelines that keep the model sharp as your data grows.
How it works
Four steps, no surprises.
You always know what we’re doing, why, and what comes next.
- 01
Assess
Is training needed at all? We set a baseline with existing models first.
- 02
Prepare data
Datasets, labelling guidelines and quality checks.
- 03
Train and evaluate
Iterate against the baseline until the gain is clear and repeatable.
- 04
Deploy and monitor
Ship, watch for drift and retrain on a schedule.
Is it a fit?
A good fit if…
Since 2013 we have built, launched and run our own products — DNSChecker.org, IPLocation.io and more. Client work gets the same team and the same standards.
See our own products- General models get your domain language or format wrong.
- You need lower cost or faster responses than a large hosted model.
- Your data has to stay inside your own environment.
- You need reliable, structured predictions from your own data.
How much data do we need?
It depends on the task. Some fine-tunes work with a few hundred good examples; others need far more. We audit your data first and tell you honestly whether training is worth it.
Can you train on private data?
Yes — in an environment you control, with access limited to the people who need it.
Is fine-tuning always the answer?
No. Often better prompts or search over your documents do the job for less. We test those first and only train when it clearly wins.
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