The Codex for research: real papers from OpenAlex, PubMed, arXiv, and Wanfang, across scoping, search, reading, and drafting. Cited reviews, annotated PDFs, and posters.
Yila AI is a tool designed for researchers who work with scientific papers, data analysis, and presentation materials. It facilitates tasks from literature search and review to data analysis and creating conference-ready outputs. It emphasizes grounding outputs in real papers and provides editable exports suitable for academic work.
The system profiles uploaded data, suggests analysis paths, and returns results, charts, and reusable files. Users can upload CSV or XLSX files, and Yila AI outlines the analysis route before delivering interpretable results and exportable outputs.
Users can generate figures from natural language prompts, edit figures in the browser, and export them as editable files. The tool also offers literature reviews with citations and editable structure, built around full papers rather than encyclopedic summaries.
Yila AI presents step-by-step guides and use cases, showing how to move from literature searches to data analysis and presentation deliverables.
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