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Improving the quality of HRIS data

We have developed solutions that rely on AI to offer innovative approaches to exploiting HRIS data.

Use of competency frameworks

For a significant player in the industry, we cleaned up the data contained in an exhaustive repository of skills. We performed this data cleaning mission in just a few days thanks to our Smart Data Quality tool and its duplicate detection functionality.

Redesign of the data model

We supported a significant player in the industry in redesigning its HRIS data model using a service-oriented approach that combined technical and functional skills. This new data model, improved and shared with the different actors of the company, has facilitated data-driven strategies.

AI solutions for HRIS

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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