Overview
When a general model is not good enough, we build one that speaks your language. We fine‑tune and evaluate models using your approved data. We then package the result for secure, local inference, with documentation and tests so your team can run it with confidence.
What you get
Model selection and tuning plan
Aligned to licence, safety and performance goals
Data preparation
With quality checks, redaction and consent alignment
Fine‑tuned model
And tokenizer delivered for local inference
Quantised variants
For CPU or edge deployment where useful
Evaluation pack
With benchmarks, examples and known limitations
Safety layer
With prompts, filters and policy responses
Integration support
For your applications or APIs
Technical options
Base models
Strong open models for conversation, code or analysis
Formats
GPU inference or quantised CPU variants for local use
Training regime
Supervised fine‑tuning and instruction alignment
Retrieval hybrid
Model tuned to work cleanly with your private RAG
Safety and governance
Data sheet for the model and a model card that records scope, licences and limits
Red‑team prompts and adversarial testing focused on your domain
Guardrails for sensitive topics and response templates for policy alignment
Clear ownership. You own the fine‑tuned artefacts and weights under agreed terms
Delivery process
Scoping
Objectives, data sources, metrics, acceptance criteria
Preparation
Data cleaning, consent checks, sampling and splits
Training
Experiments, checkpoints, evaluation and selection
Handover
Deployment bundle, docs, examples and training session
Follow‑up
Optional maintenance for updates and new data
Initial deliveries are often 6 to 12 weeks depending on data volume and validation.
Example use cases
Banking
Credit policy assistant that understands your risk language
Healthcare
Clinical guideline summariser with safe output and references
Legal
Clause rewrite assistant tuned to your style library
Engineering
Code assistant trained on your internal frameworks
What success looks like
Higher accuracy on your test sets than a general model
Lower latency and cost for local inference
Clear behaviour under edge cases with known safe fallbacks
Frequently Asked Questions
Will the model leak our data?
No. Training uses your approved data under contract and the delivered model runs locally.
Can you host it for us?
Yes, if you prefer. We can also deploy in your private cloud.
How often should we retrain?
We recommend a quarterly review or when material changes occur in your corpus.
Own a model that knows your domain
Discuss your requirements with our AI team. We will outline a clear plan and cost.