By Nataliia Koval – Director of Innovation Medirent
Artificial Intelligence (AI) in the social sphere has the potential to significantly enhance the effectiveness of providing support. By processing large volumes of data and analyzing multiple factors, AI can quickly and accurately identify citizens’ needs, automating decision-making processes. However, the primary challenge for AI in this field is the data itself.
The social sphere contains complex data arrays about citizens, including not only basic information such as passport data and family status but also more specific details like disability status, income levels, housing conditions, and other needs for social support. Furthermore, this data is often stored across various institutions in different formats—on paper or in legacy IT systems and distributed local databases.
For AI to function effectively, social data must be consolidated, structured, adapted, and accessible in real-time. This is exactly the task that Medirent’s multifunctional software and hardware complex successfully addresses, and it is actively used in Ukraine’s social sector.
How does Medirent’s technology work?
The technology developed by Medirent integrates several solutions that efficiently consolidate data from different sources and formats, transferring it in a standardized format to a unified digital ecosystem. Conceptually, the technology operates like a “socket” where data from various systems can be connected, ensuring its automatic transfer to the information core.
Key Technologies:
- Retroconversion — transforming paper archives into digital format.
- Migration — transferring data from disparate information systems.
- Integration — real-time data exchange with government registries and databases to ensure the information’s relevance and accessibility.
These technologies create a unified mechanism for retrieving required data in the format needed by different information systems within the social sphere, forming the information core of such systems according to their specific features and intended purpose, while also ensuring the efficiency of corresponding business processes.
Medirent’s technology has proven its effectiveness in practice by creating social and pension Big Data. Notable examples include the Integrated Complex Information System of the Pension Fund of Ukraine (IKIS) and the Unified Information System of the Social Sphere of Ukraine (UISSS). IKIS automates all pension processes in Ukraine. The core of the system is the Register of Insured Persons, which covers 10 million pension recipients and 20 million working individuals.
In the case of UISSS, the system ensures the automation of almost all aspects of social support. Its core, the Unified Social Register, covers 20 million recipients of various types of social assistance. The system conducts 12 data exchanges between government registries and databases, processing 15 types of social benefits.
In these two systems, the information core is created through retroconversion of paper archives, data migration from disparate systems, and continuous information exchange with government registries and databases.
The key point is that thanks to Big Data, AI is starting to work effectively in these systems: IKIS has already implemented multi-factor identity authentication using AI, and the pension AI in the chatbot is in its final stages of launch. Similar solutions are being implemented for UISSS. Therefore, Medirent has developed a universal technology that is not limited by language, sector, or legislation, ensuring its flexible adaptation to any requirements.
Join us at ESSC 2025 in Aarhus (Denmark) on 22-25 June, and visit the Medirent booth to discuss real cases and technologies already in use in Ukraine. On June 23, in the innovation zone, we’ll showcase how clean data becomes the foundation for effective AI work in the social sphere.