Paper Banana

Paper Banana is an AI academic illustration platform built for researchers, university students, and educators. It exists because traditional drawing software has a steep learning curve and a fiddly layout process, and most academics need figures fast. You describe the diagram you want in ordinary text, choose an academic visual style, and the platform plans, renders, and cleans up the result. The pipeline runs five agents: a Retriever, a Planner, a Stylist, a Visualizer, and a Critic, which is there to keep charts accurate, clear, and presentable. Beyond single figures, it converts a PDF paper into a conference poster following the IMRaD structure, and it includes a figure editor for multi-panel layouts and microscope image annotation. A free trial is offered, with paid academic plans for heavier use.

- Turn a written method or system description into a scientific figure

- Generate flowcharts, technical pattern diagrams, concept maps, and logical architecture diagrams

- Export editable SVG vectors and adjust labels, layers, and colors

- Build a conference poster from a PDF paper

- Assemble multi-panel figures and annotate microscope images

- Download output up to 2048px for print and conference screens

- Researchers preparing figures for papers and submissions

- Doctoral and graduate students assembling thesis and report visuals

- Lecturers and professors turning abstract concepts into teaching diagrams

The free trial is limited and academic plans are a recurring subscription, so check the cost against how many figures you actually need per paper. Generated figures still need a domain expert to read them: the pipeline improves layout and clarity, but it cannot verify that your method is drawn correctly. Unusual or highly specific diagrams often need heavy manual editing after generation. The platform is young, so style coverage and templates may not match every discipline, and you should keep a fallback editor for the final submission version.