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Eliminate irrelevant elements and refine your corrective actions


Detect false online reviews and eliminate them from your benchmarks 


Improve the authenticity of the analyses you conduct and make better decisions


Benefit from a tool that instantly monitors millions of reviews worldwide

With which tools?

  • With automated review collection and analysis

    Easily collect data from the world's largest review and e-commerce platforms.

  • With automatic detection of false reviews

    With a combination of three techniques: Natural Language Processing (NLP) for comment analysis, spectral partitioning for users and outlier detection for time series.

  • With decision support

    With detailed analyses, you get reliable data and insights that show where you can improve.

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Our publications


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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Introduction to OpenStreetMap: How to leverage…

In this article, we explore the use of OpenStreetMap for extracting geospatial data and implementing an approach to enhance the overall data quality. We delve into the key steps of data extraction including selecting the area of interest, data collection, cleaning, and preparing data for future use.


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Customer churn prediction with Data Science

Thanks to Machine Learning, companies can significantly improve their activities by leveraging their data. Machine Learning is a field of study of artificial intelligence that gives an AI the ability to "learn" from data.


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