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The Lab's missions

DQ

Our challenge is to demystify data quality issues, which are often considered tedious, thanks to simple AI-powered tools that can be used directly by the Business teams.

  • Write publications around exploratory data quality topics,
  • Develop solutions to make them available to Heka.ai Data Scientists,
  • Offer an internal and external expertise service on the subject.

Our AI solutions for Data Quality

Our publications

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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.

2024

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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).

2024

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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?

2024

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