SciFig

What is SciFig?

SciFig is an AI scientific figure generator for researchers who want to turn messy source material into figures that are easier to publish, present, or revise. It accepts text prompts, sketches, references, PDFs, and photos, then produces figures with editable labels and layouts. In practice, that makes SciFig a scientific figure generator, a figure cleanup tool, and a structured editor for research graphics in one place.

The product also groups its tools and templates in a single library, so you can browse different figure generators instead of starting from a blank page every time. According to the site, new users can receive 400 free credits on day one with an invite, and GPT Image 2 is available in Text-to-Figure.

Key features

SciFig’s main strength is that it supports several different ways to create a scientific figure instead of forcing one workflow.

• Text-to-Figure: generate a figure from a plain-language description.
• Figure Enhancer: upscale, recolor, inpaint, or relabel an existing figure.
• Sketch-to-Figure: convert a hand-drawn sketch into a clean vector-style figure.
• Reference-to-Figure: redraw an existing reference image in SciFig’s publication style.
• PDF-to-Figure: extract and regenerate a figure from inside a PDF.
• Photo-to-Figure: turn a lab photo into a labeled schematic.
• Vector Canvas: edit AI figures as layered, fully editable SVG.
• By figure type: build specific research visuals such as a conceptual framework, PRISMA flow diagram, bell curve, free body diagram, graphical abstract, or syntactic tree.

SciFig also exposes model guidance inside the product. The site says GPT Image 2 is the recommended default for journal papers, Nano Banana Pro is aimed at slides and posters, and Nano Banana 2 is positioned for routine figure work.

How to use it

SciFig is designed to let you move from source material to a polished scientific figure without switching tools.

1. Pick the figure path that matches your starting point: text, sketch, reference image, PDF, or lab photo.
2. Choose a generator such as Text-to-Figure, Sketch-to-Figure, or PDF-to-Figure.
3. If you already have a draft figure, use Figure Enhancer to relabel, recolor, inpaint, or upscale it.
4. Open the result in Vector Canvas when you need layered SVG editing rather than a flat image.
5. Use the model guidance to match the output to the use case: journal paper, slides, posters, or routine figure work.
6. Browse the library if you want a template or a specialized generator for a common research graphic.

Because the app includes both generation and editing, a scientific figure generator workflow can start with rough input and end with a more controlled layout. That is useful when a sketch or PDF contains the right structure but still needs cleaner labels or a different presentation style.

Who it is for

SciFig is aimed at researchers, students, and science communicators who need a scientific figure generator that handles technical visuals rather than general-purpose art.

It is a fit for:

• researchers preparing journal figures
• people making graphical abstracts or summary panels
• teams converting lab photos into schematics
• users who already have a figure draft and need edits
• presenters building slide-friendly scientific graphics
• reviewers or authors who need cleaner redraws of references or PDFs

SciFig’s model split makes it especially relevant if you care about the end use. The site explicitly points to GPT Image 2 for journal papers, Nano Banana Pro for editorial-style slides and posters, and Nano Banana 2 for everyday figure work.

What to know before you use it

SciFig is a scientific figure generator, but it is not an automatic guarantee of publication acceptance or scientific correctness. You still need to verify labels, geometry, symbols, and factual content before submitting anything to a journal or conference.

Important caveats:

• The site mentions editable labels and layouts, but you should still inspect every layer in the Vector Canvas before export.
• PDF-to-Figure and Reference-to-Figure can only work well if the source is legible; low-quality scans or crowded pages may reduce accuracy.
• Photo-to-Figure is useful for transforming lab photos into schematics, but it does not replace manual checking of dimensions, annotations, or domain-specific notation.
• The model recommendations are guidance from the app, not a promise of perfect output for every field.
• For final submission, you should compare the generated figure with your manuscript, source data, and any journal figure requirements.

In short, SciFig is best when you want a scientific figure generator that helps you draft, redraw, and refine research visuals, while keeping a human in the loop for accuracy and compliance. Use the app to speed up figure production, then confirm the final result before you publish or submit it.