PaperBanana

PaperBanana automates the creation of publication-ready academic illustrations from natural language descriptions. It targets researchers who need diagrams, charts, and infographics that adhere to scientific standards. The tool emphasizes faithful, precise, and aesthetically polished figures produced by AI-driven visualization rather than manual drawing.

The system operates via a multi-agent framework that interprets text input, translates it into structured visual layouts, and renders them into publication-ready figures. The process focuses on translating descriptions into accurate visuals while maintaining scientific intent. Users interact with a text prompt and select a visual style, receiving a finished figure in seconds.

Core capabilities include generating methodology diagrams, statistical charts, system architectures, flow charts, and poster assets. It supports executable Python Matplotlib code for charts to ensure numerical accuracy and provides aesthetic refinements to improve color, typography, and layout for publication standards.

PaperBanana outlines plans and features across a web-based platform with tiered pricing and model access. It describes plan differences, usage limits, and features such as auto style retrieval and model access within its stated plans and integrations.

Use cases

• Methodology diagrams, statistical charts, and infographics from paper text