A model that thinks like your business — not like the internet.
Fine-tuning trains a foundation model on your proprietary data, giving you responses that match your tone, terminology, and domain accuracy — no prompt engineering workarounds required.
The Problem
Prompt engineering can only go so far. When you need an AI that consistently uses your product nomenclature, understands your internal processes, and avoids generic or off-brand responses — you need fine-tuning. RAG alone can't solve terminology drift, tone inconsistency, or the cognitive overhead of massive prompt templates.
Our Solution
Built for your business.
Deployed in weeks, not months.
We design, build, and operate the full AI system — from model selection and prompt engineering to security hardening and production deployment.
- Domain-specific vocabulary and tone baked into the model weights
- Dramatically reduced hallucination on domain tasks vs. base models
- Smaller, faster models that cost less per token to run
- Proprietary training data stays private — we train on your infrastructure
What's Included
Base models
GPT-4o mini, Llama 3, Mistral, or custom
Training data
Your documents, Q&A pairs, labelled examples
Minimum dataset
~50 high-quality examples as a starting point
Evaluation
BLEU, ROUGE, and domain-specific accuracy benchmarks
Hosting
OpenAI fine-tune API or self-hosted inference server
Iteration
Up to 3 training rounds included in engagement
Client Result
West African 3PL provider
Fine-tuned a route optimisation assistant on 3 years of freight data, enabling AI-driven routing decisions that cut dispatch time from 2 hours to 28 minutes and improved driver utilisation by 31%.
Read case study →4×
faster routing decisions at peak load
Ready to get started?
Book a free discovery call. We'll scope your requirements and have a proposal back to you within 48 hours.
Book Discovery Call →