PaperBanana

PaperBanana

Overview

PaperBanana is a research-focused workspace for creating and refining academic visuals. It brings scientific illustration, image editing, structured SVG diagrams, figure editing, paper editing, poster projects, and saved creation management into one product. Researchers can start from paper text, methodology notes, a prompt, a sketch, an existing image, or another visual reference. The result is a reviewable draft that can be revised before it is used in a paper, poster, presentation, thesis, lecture, or other research communication.

Academic visual workflows

The scientific illustration workflow helps users create visual candidates from text and reference material. Typical uses include system overviews, experimental setups, process diagrams, conceptual figures, architecture diagrams, research communication graphics, and supporting visuals for posters or presentations. Users can inspect composition, readable labels, contrast, and whether the draft still matches the source.

PaperBanana also includes structured diagram templates for flows, frameworks, roadmaps, and academic figures. These projects remain editable, so researchers can revise labels, colors, layers, arrows, and layout elements. This is useful when a lab needs to correct terminology, reorganize a sequence, or adapt a visual for a different paper section or presentation.

For existing visuals, figure and paper editing workflows support targeted changes instead of complete replacement. A user can bring in an image and describe the visual detail that needs attention. The product also includes a poster workflow based on searchable PDF papers, editable text blocks, and separate visual blocks. Researchers can review claims, numbers, captions, citations, and the relationship between text and visuals before export.

Review-oriented process

PaperBanana keeps the human review step visible. A practical workflow is to describe the needed figure, choose a suitable tool or model, generate a draft, inspect the result, revise the source or prompt, and export only after checking the details. Users should verify scientific meaning, labels, legends, units, statistics, citations, accessibility, and any rules from a journal, conference, university, or funder.

The product does not claim that an AI-generated visual is automatically accurate or accepted by a publication venue. It helps users get to a visual draft and maintain a clear point where human verification is required. A polished appearance is not a substitute for checking the underlying science.

Access and pricing

The interface supports English, Simplified Chinese, Traditional Chinese, Korean, Japanese, Spanish, and German. Accounts can begin with starter credits. Additional usage is available through monthly or yearly subscriptions and one-time credit packs. Generation actions display their credit cost before the task begins, and the live pricing page explains current purchase options.

Getting started

Choose the workflow that matches the task. For a new figure, describe the subject, components, relationships, and desired output. For a methodology diagram, include the real stages and direction of information flow. For an edit, upload the current visual and explain the specific change. For a poster, provide a searchable source paper and review the extracted content before building the layout.

Before exporting, compare the visual with the source. Confirm that components, arrows, labels, numerical values, axes, units, legends, and citations are correct. Check readability at the final display size and apply any venue rules for disclosure, resolution, fonts, dimensions, or accessibility.

PaperBanana combines AI-assisted drafting with structured editing and an explicit review loop. It helps shorten the path to a reviewable academic visual while preserving the researcher's responsibility for accuracy, clarity, data, citations, and publication requirements.