LLM fine-tuning services.
A model that speaks your domain.
Fine-tuned and distilled models for tasks where general models are too slow, costly or vague.
The problems we solve first.
Cost at scale
Large models are expensive for high-volume tasks.
Domain language
General models miss industry terms.
Latency
Some tasks need answers in milliseconds.
What you get.
Every engagement includes design, engineering, evaluation, security review and handover from one senior team.
Dataset building
Clean, labelled training data from your records.
Fine-tuning
Supervised and preference tuning.
Distillation
Smaller, cheaper models from larger ones.
Benchmarking
Before-and-after accuracy and cost.
Deployment
Hosted on your cloud or a provider.
Retraining loop
Scheduled updates as data grows.
LLM fine-tuning, by industry.
How we ship AI that holds up.
Evaluation comes before scale. You see it working on your data before you commit to the full build.
Discover
Pick the task, define what “good” means and collect sample data.
Prototype
A working version on your real data, shown to real users.
Evaluate
Automated tests for accuracy, latency, cost and safety.
Productionise
Security, scaling, integrations and admin controls.
Monitor
Quality, drift and spend tracked; prompts and models improved.
Three ways to start.
AI sprint
One use case, prototyped on your data and tested with users.
You leave with · Prototype + go/no-goPilot
A production-grade version for one team, with evals and monitoring.
You leave with · Live pilot + ROI dataAI team
A dedicated squad that ships and improves AI across your products.
You leave with · Roadmap deliveredQuestions, answered.
Most clients start with a two-week AI sprint. Pilots and production builds are priced after the sprint, once we know what works on your data.
Ready to try llm fine-tuning? Start with a sprint.
Tell us the task. An AI architect replies within one business day with a sprint plan. NDA on request.