Innovative contribution of a Ukrainian IT developer to the creation of digital products for a new generation of business
Keywords:
B2B, artificial intelligence, business process automation, digital platform, small businessAbstract
The article examines the role of digital technologies in the transformation of business processes in the B2B segment, in particular through the use of innovative solutions, such as platforms for automation of orders and communications. The impact of artificial intelligence on reducing costs, increasing the accuracy and speed of interaction between enterprises, as well as optimizing internal processes is analysed. Vitaliy Yasenenko, an experienced IT specialist and entrepreneur, has developed the Trego platform, which brings together suppliers and customers in a single digital environment, allowing you to automate and optimize interaction processes. The creation of such products was a response to the real problems of Ukrainian business, in particular due to the reduction of dependence on foreign platforms. Another tool is also introduced – Issist, a free platform for small businesses that automates the processes of booking customers through a Telegram bot. Technologies that help increase the efficiency and competitiveness of enterprises in conditions of war and economic instability are evaluated
References
Yasenenko, V. (2025a). Application of deep neural networks to automate production quality control in real time. Information Technologies and Computer Engineering, 22(2), 157-169. https://doi.org/10.31649/vitce/2.2025.157
Yasenenko, V. (2025b). Cyber defence automation: Can AI outperform hackers?. Technologies and Engineering, 26(3), 89-99. https://doi.org/10.30857/2786-5371.2025.3.7
Yasenenko, V. (2025c). Development and testing of the effectiveness of hybrid cryptographic algorithms for protecting personal data in mobile applications. Bulletin of Cherkasy State Technological University, 30(3), 24-36. https://doi.org/10.62660/bcstu/3.2025.24
Yasenenko, V. (2025d). Evaluating the effectiveness of image recognition systems for automatic detection of malicious files based on image metadata. Bulletin of Cherkasy State Technological University, 30(2), 77-87. https://doi.org/10.62660/bcstu/2.2025.77
