01 · AI Solutions
AI Model Training
Teaching the model from prepared data, with every run recorded so results can be reproduced.
AI Solutions
AI Model Training
Teaching the model from prepared data, with every run recorded so results can be reproduced.
Showing 1 of 5
- 1Prepare and split data
- 2Label and review
- 3Train
- 4Tune
- 5Record and version
What We Do for You
- Prepare and split your data properly.
- Label examples with written guidelines and agreement checks.
- Train and tune, recording every run.
- Keep results reproducible months later.
- Show the compute cost before training begins.
How this is bought: Bought as a defined project: fixed scope, agreed milestones, handover and training. Build an estimate for your case.
Our Approaches Explained
Dataset splitting
Separate training, validation and test sets, kept apart so results are not flattered.
Labelling and annotation
Human-labelled examples with written guidelines and agreement checks between labellers.
Fine-tuning and transfer learning
Starting from a trained general model and adapting it to your domain with far less data.
Hyperparameter tuning
Systematically searching the settings that control learning, rather than guessing.
Class imbalance handling
Techniques for the case that matters but rarely occurs - fraud, failure, rare disease.
Experiment tracking
Every run recorded with its data version, code version, settings and result.
Reproducibility
Fixed random seeds and versioned data so a result can be recreated months later.
Compute and cost planning
Choosing hardware and run sizes deliberately, with cost visible before training starts.
The Standards We Work To
PyTorch and TensorFlowscikit-learnMLflow-style experiment trackingData and model versioning (DVC-style)LoRA and parameter-efficient fine-tuning
We follow the structure and controls these standards describe. We do not claim to be certified against them - where you need a formal certificate, we prepare the evidence and an accredited body performs the audit.
What You Get
- Labelled dataset with guidelines
- Training pipeline
- Experiment log
- Trained model artefact with version
- Cost and compute record
Runs fully reproducible94%
Labelling agreement checked88%
Experiments logged100%
These are the areas clients most often ask us to improve. Your project sets its own targets, measured and agreed with you.