Аналіз існуючих мультимодальних ботів у telegram для оцифрування та систематизації рукописних текстів

Abstract

This work analyzes existing multimodal Telegram bots for digitizing and systematizing handwritten culinary recipes. As digital transformation grows, converting paper archives into structured knowledge bases becomes increasingly relevant. The study examines bots such as OCRBot (image to text), Argus, Tasty Cooking Bot, and AI Chef Bot, comparing their text recognition and content organization capabilities. While OCR bots extract text from images, they lack semantic structuring, and culinary bots work only with pre-existing content without multimodal input. This analysis identifies the key functional gap between digitization and intelligent organization, which should be addressed in future integrated solutions