PaperBanana (paper-banana.ai)

PaperBanana automates the creation of publication-ready diagrams and plots from raw scientific content. It targets researchers who need visuals for papers, presentations, or teaching materials. The tool provides an automated workflow that translates methodology, data, or concepts into professional illustrations without requiring design skills. It manages the illustration process through a system of agents that collaborate to produce accessible visuals suitable for academic contexts.

PaperBanana operates as an agentic framework that orchestrates specialized agents to transform raw scientific content into publication-quality diagrams and plots. It retrieves reference examples to guide style and content, ensuring style alignment with academic standards. The system relies on a multi-agent approach where distinct roles handle retrieval, planning, styling, rendering, and critique, with iterative feedback to refine results.

PaperBanana offers multiple illustration types and output options. It supports methodology diagrams, statistical plots with executable Python code, aesthetic enhancements, and educational infographics. Outputs are designed to be downloaded as high-quality figures ready for inclusion in publications and presentations. The platform emphasizes reference-driven style, iterative refinement, and publication-ready results.

PaperBanana provides plans with different credit quantities and speeds and lists platform and integration notes. It mentions sign-in with Google, high-resolution downloads, and outputs suitable for LaTeX or Word documents. The pricing page shows tiered credits per month, with annual savings and various features for individuals, active researchers, and institutions.

Use cases

• From methodology diagrams to statistical plots and infographics, PaperBanana handles it all.