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    Use AI to activate your data

    Data must be used wisely to support decision-making, enable anticipation, and also optimize costs.

    Since HR data is often insufficiently exploited, our joOb AI solutions offer the possibility of unprecedented analyses and correlations.

What tools are available?

  • Job Observatory

    Leverage data from job postings on the Internet, using NLP techniques to analyze labor market trends at skill and job level.

  • Predictive management

    Build and analyze the impact of resource projection scenarios supported by historical developments. These scenarios and projections are a significant lever to adjusting your HR strategy. Get an analysis of internal and external mobility flows and optimize the actions to be implemented to meet your objectives.

  • Mobility

    Identify the most suitable profiles for a job offer or project based on their skills and experience.

  • Talent management

    Evaluate employee profiles to direct them towards the most relevant offers and training. This solution for identifying the reasons for resignation detects employees most at risk of resigning.

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Our publications


Boosting search engine capabilities of RegReview:…

RegReview is an AI solution for compliance teams, to automate regulatory monitoring and processes, which brings together several tools, the most essential of which is a search engine operating on a compiled database of custom-built regulatory sources.

The database contains ~300k documents.


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Article title

Labeling text clusters with keywords

We propose to explore several keyword extraction techniques to label text clusters obtained after a Text Clustering or a Topic Modeling pipeline. This work is following our previous articles about Topic Modeling and Text Clustering (here and here).


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Synthetic data or how to share sensitive data…

For a period of six months, 5 students from Centrale Supélec and ESSEC worked collaboratively with Sia Partners on building a Python library to create fake - which we'll call synthetic - data.
But what's the point of creating fake data? How could it help organizations?


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