What we do
General-purpose LLMs know everything broadly but your domain shallowly. Fine-tuning adapts a pre-trained model to your specific vocabulary, tone, task format, and domain knowledge — producing dramatically better results for specialised applications. We fine-tune models using your data on Azure, with full GDPR compliance.
Ideal for
Organisations with labelled domain data who need better accuracy than prompt engineering alone can achieve for a specific task
Common applications
Domain-Specific Text Classification
Fine-tune a classification model on your document categories — legal, financial, clinical — achieving accuracy that general models cannot reach.
Entity Extraction for Your Domain
Train a model to extract domain-specific entities: contract clauses, financial metrics, medical codes, or product attributes.
Tone and Style Alignment
Fine-tune generation models on your organisation's writing style for consistent brand voice in automated content.
Task-Specific Instruction Tuning
Instruction-tune models for specific business tasks: contract review, document summarisation, or structured data extraction.
Smaller Model Distillation
Distil a large capable model into a smaller, faster, cheaper model for high-volume production inference.
Self-Hosted Model Fine-Tuning
Fine-tune open-source models (Mistral, LLaMA) on your data for complete data sovereignty at lower cost than Azure OpenAI.
How we work
Task & Data Assessment
Evaluate whether fine-tuning or prompt engineering better solves your task. Assess training data quality and volume.
Dataset Preparation
Clean, format, and split your training data into train/validation sets with quality checks.
Training & Evaluation
Run fine-tuning on Azure ML or Databricks. Evaluate against held-out test set and compare to baseline.
Deployment & Monitoring
Deploy the fine-tuned model with performance monitoring. Establish a retraining cadence.
What you receive
- Fine-tuned model weights and training artefacts
- Dataset preparation pipeline
- Evaluation report comparing fine-tuned vs. baseline model
- Inference endpoint deployment (Azure ML or AKS)
- Retraining pipeline with trigger logic
- Full documentation and model card
Ready to get started?
Let's discuss your requirements. No commitment, no sales pitch — just a focused conversation about your situation.
Book a free discovery call