A visual Brain-Computer Interface (BCI) speller is a system which assists disabled persons with severe neu-romuscular diseases to communicate with the external world. It acquires brain signals in response to visual stimuli shown to the person on a screen, and then analyzes in real-time to predict the desired symbol on a single trial basis. To date most BCI design paradigms have been focused on the development of a speller to communicate English or Latin based languages. Due to a lack of BCI spellers for patients speaking Cyrillic-based languages, this study presents the initial design and evaluation of a speller that contains Cyrillic alphanumeric characters. The visual BCI speller was evaluated on five healthy subjects, who showed encouraging results during both the offline training phases, as well as during the real-time BCI spelling experiments. We discuss each steps of the design in detail and share the challenges and limitation of such design approaches with possible solutions.