Data Science and machine learning are used to enhance capabilities of business-driven software.
Our data scientists and engineers use statistics, mathematics, and cutting edge techniques
to build models that collect data and generate actionable insights for businesses
to enhance targeting, increase business efficiency, and maximize sales.


  • Data Science in Software Development


  • Machine Learning Technology in Software Development


  • Artificial Intelligence Software Development Services


  • Computer Vision Technology


  • Oleksii Ostroverkhyi, CCO MobiDev, PhD Systems and Means of Artificial Intelligence

    Oleksii Ostroverkhyi

    CCO MobiDev

    PhD Systems and Means of Artificial Intelligence

    "Data science is no rocket science if we have data and a clear picture of the problem we are trying to solve. From the very start of a project, data analysis is performed with business goals in mind. Understanding of these goals allows us to analyze data effectively. This is the key to further selection of technologies, the way we build models and make them learn. This is the approach that will enable use of data to generate business value."

  • Yuriy Luchaninov, JavaScript Group Leader

    Yuriy Luchaninov

    JavaScript Group Leader

    "Most ML frameworks—such as Keras and TensorFlow—allow to export models in their specific formats. Another possible approach is ONNX – Open Neural Network eXchange format. It provides interoperability between different open-source ML frameworks and allows to combine various approaches to bring continuous efficiency to the product."

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    • Data Science Programming Languages: Python, R, C++, Go

      Languages: Python, R, C++, Go

      Data science and machine learning solutions can be written in a number of languages, selected in accordance with project specifics.

    • Machine Learning Framework TensorFlow


      This machine learning framework has a flexible architecture, while its computations are based on the graph theory and neural networks.

    • Machine Learning Technology Keras


      High-level neural networks API, written in Python with a focus on enabling fast experimentation. It is capable of running on top of such tools as TensorFlow, Theano, or CNTK.

    • Open Neural Network eXchange (ONNX)

      ONNX (Open Neural Network eXchange)

      This is an open source format for deep learning models. It allows AI developers to form state-of-the-art tool sets throughout a continuous cycle of project evolution.

    • Cloud Solutions for Data Science, Machine Learning, Artificial Intelligence

      Cloud Solutions:
      CloudAI, Azure, Watson

      These are the most popular cloud services, available for training of DS/ML/AI models and further integration. They can either use your custom data or be trained with their own datasets.

    • Mobile Machine Learning

      Mobile Machine Learning:
      CoreML, TensorFlow Lite, Cafe2Go

      A number of frameworks can be used to integrate existing machine learning models with mobile applications.

    • Computer Vision Software: OpenCV, Dlib

      Сomputer Vision
      OpenCV, Dlib

      This comprises 4 main parts: recognition algorithm, data for learning, resources for computation, and integration with software solutions.

    • AI-based Conversational Interfaces

      AI-Based Conversational Interfaces

      These solutions requires time, computational power, and huge amounts of relevant data. In most cases it is reasonable to integrate new products with existing solutions offered by major cloud providers.


Data Science Project Development
  • Prediction and facilitation of sales in the retail sector

    Prediction and facilitation
    of sales in the retail sector

    Applied Data Science helps retail businesses to increase sales and conduct market research. Models predict customer demands, help optimize pricing, and improve retention policy. Here are some of the features implemented in our latest ERP solution.

    • Weekly demand predictions to maximize gross income
    • ABC/XYZ analysis for classification of products by stability of sales and in relation to total income
    • Optimization of targeted discounts via division of goods into specific groups
    • Customer basket analysis to offer relevant accompanying goods
    • Anomaly detection will be applied for enhanced security and prevention of fraudulent transactions
  • Face and voice recognition
    for smart authentication solutions

    Data Science works with face recognition for various purposes, including advanced authentication systems, intruder detection, and identification of customers. These solutions bring secure and convenient experiences of accessing personal data.

    • Face and voice recognition models that eliminate data breach risks
    • Antispoofing and anomaly detection for confident and stable operations
    • Optimization and fine tuning of trained models for high accuracy
    Face and voice recognition for smart authentication solutions
  • Machine Learning for human behavior prediction

    Recommendation systems
    for effective targeting

    Custom solutions can be empowered with personalized recommendations based on statistical methods and machine learning techniques. A number of models were created and applied by our team as support modules for a complex dating application based on psychology of human behavior and relationships.

    • Recommendation models with prediction of user behavior based on extensive analysis of gathered data
    • One of the modules is responsible for supporting relationships with periodic surveys, advice on things that require extra attention, as well as general recommendation on relationship behavior
    • In the near future, social profiles will be used for even more detailed social portrayals of users in order to improve precision of recommendations
  • Computer vision for medical imaging,
    AR/MR/VR solutions

    Augmented and mixed reality devices have already entered the healthcare sector with pioneering software solutions. Now they can be enhanced by means of Data Science and computer vision.

    • Analysis of various types of medical images, including MRI, X-ray, CT, ultrasound, and molecular images
    • Data Science and machine learning can be used for detection and positioning of objects in augmented and virtual reality solutions
    • Custom solutions that go beyond standard capabilities of available toolkits
    Computer Vision for Healthcare
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