A model that speaks your business.
In plain wordsAI models tailored to your business using your data, deployed according to your control and confidentiality requirements.
The challenge
General-purpose models do not know your products, your terms or your rules. And some of your data cannot leave the company.
- Answers that miss your vocabulary and your context
- Sensitive data that cannot go to external AI services
- Usage costs that grow with volume
- Dependence on a single provider’s model
What we do
Fine-tuning of existing models
An open-source or commercial model adapted to your data and your tasks, so it answers the way your business needs.
Specialised models
Smaller models trained for one task: classifying, extracting, scoring, detecting. Fast and economical to run.
Private deployment
The model runs in your cloud or on your servers. External connections are defined and controlled with you.
Evaluation on your cases
Quality measured on your real examples, before and after adaptation, then followed in production.
A model tailored to your business
Rights to deliverables are specified in the contract, subject to the licences of the models used.
Your data
It stays in your environment, during adaptation and in use.
Your model
Usage rights, access to weights and transfer options depend on the contract and the licence of the selected model.
No lock-in
The model can be moved, replaced or adapted again, by us or by another team.
Controlled costs
A model sized for its task often costs much less to run than a general one.
Examples of use cases
Typical situations where a custom model is worth it.
A model for regulated data
- Context
- Health, finance or HR data cannot be sent to external AI services.
- Outcome
- An open-source model adapted and deployed in the company’s own environment. No data leaves it.
Your technical vocabulary
- Context
- A general model confuses product references and technical terms specific to the company.
- Outcome
- A model adapted on your documentation, which uses your terms correctly, measured on real questions.
Classifying large volumes at a lower cost
- Context
- Large volumes of documents or messages to classify each month, with a general model that is slow and costly.
- Outcome
- A small specialised model, as accurate on this task, faster and cheaper to run.
Less dependence on a single provider
- Context
- A critical feature depends entirely on an external provider’s model.
- Outcome
- An equivalent model hosted by the company, with the option to switch between the two.
Expected results
- A model that understands your business
- Sensitive data kept in your environment
- Running costs suited to your volumes
- A model you own and can move
From a general model to yours
- 01
Define the task
What the model must do, on which data, and how its quality will be measured.
- 02
Prepare the data
Examples selected, cleaned and annotated with your experts.
- 03
Adapt and evaluate
Fine-tuning, then comparison with the general model on your real cases.
- 04
Deploy privately
Installation in your environment, monitoring, and new adaptation when your data changes.
Included in every project
What comes with every projectData
Gathering, cleaning and structuring your data. It is the foundation of every AI project that works.
Security & compliance
Data under your control, hosting on your premises possible, traceability and controlled access. The GDPR, Japan’s APPI and Hong Kong’s PDPO are taken into account, and we adapt to your own security requirements and audits.
Operations & quality evaluation
Monitoring in production, measurement of the quality of the AI’s answers, guardrails, continuous improvement and cost control.
Training & handover
Training for executives and teams in AI, transfer of skills, documentation.
Does your business need its own model?
Tell us about the task and the data. We will tell you whether adapting a model is worth it, or whether an existing one is enough.