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Doc Review automatically identifies, extracts and structures essential information in your documents:

contracts, invoices, briefing notes, etc.


    Upload your documents, ask questions, get answers

    Convert all your documents (contracts, invoices, memos...) whatever their format (PDF, Scan, Images, Word ...) into structured and usable text.

    Easily define the key elements to be extracted according to your needs (signatories, specific clauses, pricing conditions).
  • Annotate the results: AI adjusts the solution to your context

    View the results on a straightforward interface, export them or interface them with your other tools.

    Screen DocR 2
    Thanks to our annotation feature, capitalize on your teams' knowledge for a continuous improvement of the AI.

Have a look at Doc Review

Get better operational results

  • Better efficiency

    Reduce the mental load of your teams by freeing them from these unstimulating and time-consuming tasks.

  • Time saving

    Save time and devote it to more strategic activities for the company.

  • Removing errors

    Take full advantage of all the data in your documents and eliminate any risk of error!

  • Optimization

    Enhance the quality of your data and improve accuracy, organization, and efficiency.

They trust us

  • Banking actor

    As part of its actuarial activities, the bank receives a significant volume of reporting files containing key indicators. However, these data are contained in different document formats and in many different forms (tables, figures, text fields, etc.). Searching for this data can be tedious without a suitable tool. With Doc Review, we offer a tool for intelligent extraction of the key indicators that Pacifica needs to pre-populate a UCITS monitoring file.optiwioperation

  • FMCG actor

    Management of the entire billing process. The tool allows the decoding, analysis and classification of information contained in raw invoices in disparate formats, to restore them in clear, exploitable and scheduled data.

  • Financial agency

    Databases optimization and enrichment with essential elements. It allows the processing of a greater quantity and variety of data, sources, and document formats. Users can also isolate the most important elements according to their own criteria to build more robust reports based on extractions.

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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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