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Let AI detect your duplicates, clean, complete, and enrich your data within a single solution.

Functionalities

    Increase your data quality

    Find all the data quality features:

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    • Deduplication
    • Outlier detection
    • Normalization on a sizable functional perimeter (address, bank details, customer details, etc.)
  • Leverage the power of machine learning

    Let AI adjust processing to your context and optimize your automatic processing with the annotation tool.

    Screen SDQ 2
    Turn your data into opportunities: enrich it with other sources of information (internal data, open data, etc.) to better target your prospects or interventions, imagine new offers, develop operational performance, etc.

Have a look at Smart Data Quality

Mobilizing your data has never been easier

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    Better accuracy

    Diagnostic accuracy of 95%.

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    Optimized integration

    Data quality processing is generated in a few clicks and natively integrating your business rules

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    A full interfacing service

    Compatible with your existing tools

THEY TRUST US

  • UTILITIES COMPANY

    We cleaned up the customer database as part of a CRM migration by deploying Smart Data Quality, a solution by Sia Partners, on AWS Cloud.

  • ENERGY DISTRIBUTOR

    We enriched customer data with Open Data to refine customer segmentation.

  • GAS SUPPLIER

    We enriched their data with those of social landlords to identify social housing and prioritize the maintenance of connections on its network.

  • WATER NETWORK OPERATOR

    We enriched customer data with median incomes, household composition, and garden sizes to better understand water consumption and design new service offerings accordingly.

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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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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).

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

Read more