Scholix was born from a simple frustration: too many good papers get rejected for fixable reasons. We built an AI-powered platform that gives every researcher access to the kind of feedback that used to be reserved for those with senior supervisors and insider journal knowledge.
Academic publishing is broken for early-career researchers. A paper that deserves to be published often gets rejected not because of the ideas, but because of fixable technical issues — poor journal selection, weak methodology framing, or missing citation context. Scholix levels the playing field by giving every researcher access to AI-powered pre-submission review that identifies these issues before a reviewer ever sees them.
Our analysis is grounded in real acceptance data from 200+ journals and trained on thousands of published papers across 15 disciplines. We don't guess — we calculate.
A full peer-review simulation, journal match, and acceptance score in under 60 seconds. Because researcher time is too valuable to waste on slow tools.
Your research is yours. We don't store paper content beyond what's needed for analysis, and we never share your work with third parties or use it to train models.
Scholix was built combining state-of-the-art AI (Claude by Anthropic) with deep academic expertise. Our prompting and scoring frameworks were developed with input from researchers, journal editors, and PhD supervisors across medical sciences, engineering, social sciences, and computer science.
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