001 Data Science & Modeling

Exploratory analysis and advanced data processing make it possible to prepare reliable and usable data sets. This solid foundation makes it easy to design and train supervised and unsupervised machine learning models. These approaches are implemented for anomaly detection, forecasting, scoring and segmentation.

002 Deep Learning & Advanced AI

Neural networks are mobilized for use cases in computer vision, such as image recognition or OCR. At the same time, natural language processing (NLP) makes it possible to develop semantic search engines, intelligent chatbots or automatic summary solutions. Generative AI, whether text, image, or code, is exploited to create innovative and differentiating solutions.

003 MLOps & Industrialization

Deploying models in production with CI/CD ML pipelines. Monitoring, retraining and governance of models. Containerization of models and integration into microservice architectures.

004 Ethics & Compliance

The Explainable AI (XAI) approach ensures transparency and understanding of algorithmic decisions. This approach is in compliance with regulations such as the RGPD or the IA Act. It is complemented by the establishment of ethical charters and responsible frameworks in order to guarantee the controlled and reliable use of artificial intelligence.