This paper presents a novel approach to the problem of stress placement in Russian text, with a particular focus on resolving homographs. We introduce a comprehensive system that combines morphological analysis, context-aware neural models, and a specialized “Ё-fikator” to accurately place stress in Russian words, including those with ambiguous pronunciations. Our system outperforms existing solutions, achieving a 0.96 accuracy on homographs and 0.97 accuracy on non-homograph words.