Information system for The Ministry of Education and Science of Ukraine

Why They Chose Us

The Ministry of Education and Science of Ukraine approached us with a task to develop an advanced information system for the collection and analysis of financial and statistical data on the activities of higher education institutions. The previous contractor’s performance was unsatisfactory, prompting the client to seek a new partner with expertise in real-time data processing and AI-powered solutions.

Our company was recommended to the client based on our successful track record with AI technologies, including automated data processing, predictive analytics, and real-time decision-making tools, which ultimately convinced the client to choose us for the project. Our goal was to create a system that could efficiently collect, process, and store data, as well as generate dynamic reports. We implemented AI-driven technologies, including machine learning algorithms and real-time data analytics, to ensure that the collected data could be analyzed in a meaningful way and used for decision-making. This would enable the Ministry to effectively manage resources and improve the accuracy of financial assessments.

What Challenge Needed to be Solved?

Our task was to build a system capable of gathering reliable, evidence-based financial and operational data and structuring it for decision-making in real time. AI technologies were key to ensuring that the system could handle vast amounts of data and deliver insights quickly. We had to automate data processing and generate reports within 10 seconds, reducing the manual work required to handle reports. The data, including financial and operational statistics for universities, educational levels, and specialties, had to be processed intelligently to help decision-makers assess the financial state of universities, monitor budget efficiency, and optimize higher education costs.

What Obstacles Did We Encounter?

We faced challenges with integrating data from various sources in real-time, especially when some of these sources lacked direct API support. AI-driven solutions, including web crawling and machine learning-based data processing, were crucial for extracting data from diverse formats like text and Excel files. We also had to address issues of data validation, structuring, and real-time reporting, all while adhering to tight deadlines. The initial plan was to collect data from sources with readily available APIs, but we encountered delays as not all government agencies could provide the required API access. As a result, we leveraged AI technologies like web scraping, natural language processing (NLP), and machine learning models to automate data extraction and processing, ensuring that the system could work with multiple, less accessible data formats.

What Should the Ideal Solution Look Like?

The ideal solution needed to efficiently collect, process, and store data while ensuring that reports could be generated in real-time. By integrating AI technologies, such as machine learning models for data classification and predictive analytics, we ensured that reports were generated automatically based on real-time data, removing the need for manual input. This made decision-making faster and more accurate for government officials, helping them allocate resources more effectively.

What Technologies Have We Chosen and Why?

We adopted an AI-powered approach that included machine learning algorithms for real-time data processing, predictive analytics, and intelligent reporting. The system used a microservice architecture to integrate various components, including the AI-driven data analysis layer. The project technologies included MySQL, Redis, RabbitMQ, Hadoop, Laravel & Python, Talend Open Studio, and Vue.js. For the AI components, we implemented machine learning models that helped classify and analyze data, ensuring fast and reliable decision-making.