Data2Paper

Interesting approach to X — how do you handle Y use case?

nice app to use and time savy

The research workflow is genuinely painful — jumping between search engines, reference managers, and writing tools is exhausting. An end-to-end AI-assisted flow could save researchers hours per paper. Would be curious how it handles citations and whether it can pull from multiple academic databases (PubMed, arXiv, Semantic Scholar). The differentiation from generic AI writing tools seems to be the domain-specific academic focus, which is smart.

Academic research today feels fragmentedsearching papers, managing references, and drafting all happen in separate tools. An AI workflow built specifically for researchers could massively reduce friction, especially if it integrates reliable citation handling and multi-source academic search.

This is a very useful idea for researchers who already have survey, questionnaire, or clinical data but struggle to turn it into a complete paper. I like the end-to-end workflow: data import, research design, analysis, writing, literature review, and AI peer review in one platform. The key question for me is transparency — can users review the selected variables, statistical methods, and citation sources before generating the final paper?

End-to-end is a bold claim — most research-AI tools stop at literature review or drafting. Curious how you handle citation accuracy, since that's usually where AI papers fall apart for academic use.

It saves a lot of time.