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Data Science

We are convinced that AI is the pillar of the new generation. The business expertise of our consultants, combined with our Data Scientists and AI products, allow us to support our customers across the universe of data to meet their business challenges.

Fraud detection on a package's journey

Fraud detection on a package's journey

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Electric consumption & production forecast

Use our models and AI databases to industrialize your forecasting models by integrating your business constraints.

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Infusing AI into all company processes

Use machine learning methodologies to increase the efficiency of your large data quality processes: cleansing, redundant data, and outlier detection.

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Factor competition into your activity with AI

Use data capture technologies to understand your competitors' pricing policies so you can incorporate them into your own calculations.

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Strengthen your risk management

Leverage datascience and advanced statistical analysis to strengthen your risk management and anomaly detection.

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Implement processes optimization with AI

Use a techno-economic optimization model to feed your strategic infrastructure implementation studies and project management.

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Build an AI-centric company

The management of a complex distribution network requires solving technical, economic and environmental challenges that can be studied from a new perspective thanks to artificial intelligence.

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Foster customer engagement

Develop a machine learning model to predict future customer churn in order to develop a marketing strategy and action plan targeting your at-risk customers.

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Anomaly and fraud detection

Leveraging AI for fraud detection helps companies to enhance internal security and in streamlining business processes.

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Operational efficiency

New technologies with artificial intelligence enable new forms of work and communication related to mobility, process automation, trend monitoring and market demand.

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Customer experience optimization

Artificial intelligence allows companies to considerably improve their customer service through various use cases.

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Impact and risk modeling

The use of AI, more specifically machine learning models, in risk modeling, helps identifying, prioritizing and monitoring risks.

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Predictive maintenance

Predictive maintenance is a method of preventing asset failures by analyzing production data to identify patterns and predict problems before they occur.

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Customer knowledge and marketing

As customers have access to information anywhere, anytime, it makes it increasingly important to collect customer insights to understand how they will behave when interacting with brands and organizations.

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Competition analysis

The use of AI for competitive analysis goes further than automating the process of collecting, organizing, and communicating information regarding your competition.

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