Data Science: boost your performance with AI and Machine Learning

Joint definition of analysis areas (mission, organization, skills, methodology, tools, delivered projects, results, ROI measurements, communication materials, risks…)

Areas for improvement across experimentation, deployment, and value communication processes. Identification, scoring and prioritization of quick wins.

Arbitration, selection and prioritization of use cases based on anticipated business contributions and ease of implementation.

Software that enables the development and deployment of predictive scores in record time.

Software that enables the building and industrialization of unsupervised customer segmentations in record time.

Software that enables the deduplication and file merging of records based on multiple search strategies.

We develop AI and machine learning-based fraud detection models, capable of identifying suspicious behavior in real time and significantly reducing false positives. Our solutions, such as Scoring.AI, adapt to the business and regulatory specificities of the banking/insurance and e-commerce sectors.

Drawing on our expertise in predictive modeling, we support Risk departments in implementing assessment and scoring algorithms, to better anticipate defaults, refine lending policies and automate portfolio management.

Our teams design behavioral analysis and complex anomaly detection systems, combining AI and business rules to identify atypical patterns linked to money laundering or terrorism financing, in compliance with AML/CFT requirements.

We activate customer data through dynamic segmentations, propensity or churn scores, in order to optimize offer personalization, commercial prioritization and customer retention. We have developed Segmentation.AI, which enables rapid, no-code industrialization of these analyses.

We design predictive models to anticipate demand fluctuations, optimize inventory, procurement or production schedules, by incorporating exogenous variables (weather, economic context, promotions, etc.).

We ensure the reliability of your data through deduplication, normalization and enrichment solutions (such as Foozydedup.AI), combining business rules and AI models to improve the quality of reference databases and enhance algorithm performance.

We integrate AI into business workflows to automate time-consuming tasks: document processing, automatic classification, information extraction, intelligent assignment, and more. The goal: to increase productivity and service quality.

We develop predictive maintenance algorithms capable of anticipating failures in industrial equipment, vehicles or networks, by leveraging IoT data to reduce downtime costs and optimize maintenance planning.