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Document Management Tool

Technology

Software Development
Data Science

Industry

Fintech & Crypto

Machine learning-powered text recognition
tool for smooth document processing

Our client is a large-scale hedge fund based in New York City, USA. The company processes a massive amount of documents every day to analyze market trends and increase the accuracy of management decision-making. To accelerate this area of analytics, our client was looking to build a tool that would assist in gathering data from PDF documents.

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Challenge:Unlock and extract data from PDFs

The project’s goal was to develop a backend tool able to recognize text formatted as a PDF table to allow the automated processing of data contained in PDF files. The tool would convert a PDF into CSV or other formats that could be parsed by analytics tools used by our client to generate valuable insights from available data.

PDF is one of the most popular formats for reports today thanks to its guarantee of compatibility across different applications. One of our experienced software engineers was designated to help the company boost its analytics capabilities and beat the competition. Our developer analyzed the problem and delivered a proof of concept (POC) to be added to our client’s analytics solution.

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Solution:Convert PDF files into structured data

The solution developed by our engineer consists of two components. The first one converts PDF files into a binary format that can be processed by a backend programming language. The second one uses a host of different criteria to identify and parse tables. Our developer equipped the solution with powerful machine learning capabilities that enable dealing with complex cases – for example, reports featuring multiple images and tables.

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Fintech & Crypto projects

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Contact us

Codete Global
Spółka z ograniczoną odpowiedzialnością

Na Zjeździe 11
30-527 Kraków

NIP (VAT-ID): PL6762460401
REGON: 122745429
KRS: 0000696869

Offices
  • Kraków

    Na Zjeździe 11
    30-527 Kraków

  • Lublin

    Wojciechowska 7E
    20-704 Lublin

  • Berlin

    Wattstraße 11
    13355 Berlin

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