ScholarViz is an AI workspace for publication-ready scientific figures. Generate graphical abstracts and figure assets, then refine with mask edits, text replacement, and editable layers. Export clean PNG or PPT for papers, posters, and slides.
Many AI image tools generate fast, but editing is painful. In ScholarViz, we decompose generated scientific figures into editable text/object/background layers so users can move, restyle, and fix details precisely. Would this be useful in your workflow (papers, posters, slides)? What s the #1 layer operation you need most?
Hi everyone, I m building ScholarViz. We re solving one painful workflow: turning research ideas into publication-ready figures without spending hours across multiple design tools. Current flow: generate with AI -> mask edit -> replace text -> decompose into editable layers -> export PNG/PPT. I d love your feedback: which step in your figure workflow is still the biggest bottleneck?
Hi Product Hunt! I’m Kyle, maker of ScholarViz 👋
We built ScholarViz because making clear, publication-quality scientific visuals still takes too much time and tool-hopping.
What ScholarViz helps with:
• Generate graphical abstracts and figure assets from plain-language prompts
• Make precise fixes with mask editing and text replacement
• Decompose images into editable layers and export to PPT/PNG
Who it’s for:
Researchers, grad students, biotech teams, and science communicators.
I’d love your feedback on two things:
1) Which step in your figure workflow is still the most painful?
2) What export or editing capability would make this production-ready for your team?
Thanks for trying it — I’ll be here all day replying and shipping improvements.
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