AI Model Development & Fine-tuning
Models that understand your business because we’ve trained them with your data.
We develop and train artificial intelligence models tailored to your use case: from fine-tuning large models to predictive models and open source solutions that run on your infrastructure.
Not every problem can be solved with a prompt. When you need precision in a specific domain, predictions based on your historical data, or a model that works without an internet connection, you have to go a step further. We develop custom models: we train large models to speak your company's language, build predictive models with your data, and deploy open source solutions on-premises when privacy or cost requires it.
What we offer
Fine-tuning large models (GPT, Claude, Gemini)
We train commercial models with your data so they generate responses specific to your industry, your terminology and your quality standards.
Predictive and deterministic models (Machine Learning)
Classic ML models for specific problems: demand forecasting, anomaly detection, classification, scoring. Robust, explainable solutions.
Open source models on-premises (Llama, Mistral)
We deploy open source models on your own infrastructure. No sending data to third parties, no recurring API costs, and total control.
Model evaluation and selection
Not every problem needs the same model. We evaluate options and recommend the simplest solution that solves your case.
Deployment and monitoring
The model’s journey doesn’t end at training. We deploy it to production, monitor its performance and retrain it whenever needed.
How we do it
We start by understanding the problem. Not every case needs deep learning or models with millions of parameters. Sometimes the simplest solution is the best one. We evaluate your data, define the right technical approach and train the model with clear success metrics. We test it under real conditions before deploying it.
We choose the simplest solution that works
We don’t use a cannon to kill a fly. If a classic predictive model solves your problem, we won’t sell you GPT fine-tuning.
Models that improve over time
Every model is monitored and retrained with new data. Accuracy improves as your business generates more information.
Total control over your models
Whether you use a cloud-based model or an on-premises one, you decide where your data runs and who has access.
Applications by industry
Legal
Legal document classification models, entity extraction from contracts, and prediction of case outcomes based on the firm’s historical data.
Retail / Ecommerce
Demand forecasting by product and season, personalized recommendation models, and customer scoring for loyalty campaigns.
Industry / Construction
Predictive maintenance of machinery, automated quality control via computer vision, and production process optimization.
Healthcare
Predictive models for patient triage, pattern detection in clinical data, and automatic classification of medical images.
Partners and technology
Frequently asked questions
It depends on the type of model. A classic predictive model can work with a few hundred records. Fine-tuning LLMs needs more, but less than you’d think. We assess this during the initial evaluation.
Yes. Open source models are deployed on your infrastructure. Commercial models depend on the provider, but we always look for the option that gives you the most control.
A basic predictive model can be in production within 4-6 weeks. Fine-tuning LLMs depends on the volume of data and the complexity of the domain.
We’ll know before deploying it. We evaluate with clear metrics throughout development. If it doesn’t meet the quality threshold, we adjust the approach before moving to production.