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February 27, 2026
10:50:55 PM
Fine-tuning & Custom ML

Custom Models

Develop AI models specifically trained on your data and optimized for your unique use cases.

Why develop a custom model?

Superior Performance

Models optimized for your specific use cases with quality results

Full Ownership

You fully own the developed model and your data remains confidential

Independence

Reduce your dependency on external APIs and control your costs

Business Precision

Models trained on your vocabulary, style and processes

Scalability

Solutions that adapt to your business and data growth

Continuous Support

Continuous model improvement with new data and feedback

Our development process

1

Data Audit & Analysis

Evaluating the quality and quantity of your data, identifying business needs and defining performance objectives.

2

Dataset Preparation

Cleaning, annotation, enrichment and structuring of your training data to maximize model quality.

3

Training & Fine-tuning

Selecting the optimal base model, supervised training, hyperparameter optimization and cross-validation.

4

Deployment & Monitoring

Secure production deployment, integration into your systems, performance monitoring and continuous improvement.

Types of models we develop

LLM Fine-tuning

Adapting GPT, Claude, Llama or Mistral to your domain with your own data for ultra-relevant responses

Automatic Classification

Specialized models to categorize your documents, emails, support tickets or content according to your criteria

Information Extraction

AI trained to automatically identify and extract key entities and data from your texts

Business Predictive Analysis

Custom algorithms to anticipate your KPIs, churn, demand or specific risks

Custom Embeddings

Vectorization optimized for your domain enabling ultra-precise semantic search

Recommendation Models

Intelligent suggestion systems based on user behavior and preferences

Content Generation

Creative AI adapted to your tone, style and guidelines to produce quality content

Anomaly Detection

Models trained on your normal data to automatically identify deviations and incidents

Frameworks & Technologies

Hugging FaceLangChainPyTorchTensorFlowOpenAI APIAnthropic APIOllamavLLM

Frequently asked questions

How much data is needed to train a model?

It depends on the type of model. For LLM fine-tuning, a few hundred examples may suffice. For classification or prediction models, we generally recommend at least 1000-5000 labeled examples. We evaluate your data during the initial audit.

How long does custom model development take?

A complete fine-tuning project typically takes 6 to 16 weeks: data audit (1-2 weeks), dataset preparation (2-4 weeks), training and optimization (2-6 weeks), testing and deployment (1-4 weeks). We often start with a 4-week POC.

Can I host the model on my own infrastructure?

Absolutely. We can deploy the model on-premise on your servers, in your private cloud, or on whatever infrastructure you choose. You maintain full control over hosting and security.

How do you handle data confidentiality?

Your training data remains strictly confidential and is never shared. We sign NDAs, apply encryption, and can work in your secure environment. The final model belongs 100% to you.

Let's develop your custom AI model

Let's discuss your specific needs and create together a perfectly adapted AI solution.