Tae Kyung Kim

Link: http://211.192.160.149:3020/ The current mainstream process for designing LLM-generated outputs (PPTs and infographics) remains quite rudimentary. ChatGPT, Claude, and Gemini (despite their recent major improvements in SVG output), along with wrapper services such as Genspark, still tend to produce designs that are only at the level of undergraduate coursework. As a result, they are largely unusable in academic and business settings. The biggest problem, however, is that generated images are essentially non- editable. To address this, I built a fully web-operable infographic image decomposer using visual grounding, text-font matching, and SVG reconstruction into editable components. When this is connected to Nano Banana’s infographic generation pipeline, it enables a workflow that is fully automated yet still supports high-end post- generation polish.