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arXiv Research Assistant Service (Human + API Hybrid)

A lightweight service where researchers submit their arXiv paper URLs (via email, Slack, or API) and receive back a curated package within 24 hours: the PDF, the Vanity HTML version, a 1-paragraph summary, and key citations extracted. The service uses a small team of research assistants (part-time or freelance) who handle the download/fetch work, plus automation for summary generation (Claude API). Researchers pay per-paper or via monthly subscription.

SERVICE

14 weeks • 70% confidence

Value Proposition

Saves 5-10 minutes per paper (download + format conversion + initial reading) AND adds real value (summaries, key citations) that citation managers don't provide. Eliminates friction entirely—researchers just send a link, get everything back ready to read and cite. Works with any citation tool, not just Zotero.

Target Audience

Busy PhD students, postdocs, and early-career researchers in STEM who read 5-20 papers/week and value time more than cost; researchers managing large literature reviews or grant proposals

Key Features

  • Email/Slack/API submission of arXiv URLs
  • Automatic PDF + Vanity HTML fetch and delivery
  • AI-generated 1-paragraph summary (Claude API)
  • And more, with full implementation detail...

Tech Stack

Node.js or Python for backend (task queue, email parsing, API) Bull/Redis for task queue management Claude API (Anthropic) for summary generation PDF.js or similar for reference extraction from PDFs
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Original Problem

Researchers waste time manually converting between paper formats when managing academic citations

Academic researchers using Zotero spend significant time manually downloading papers from arXiv and then separately fetching the HTML-rendered versions (arXiv Vanity) for better readability, creating friction in their research workflow. Current citation management tools don't automate this multi-step process, forcing researchers to context-switch between tools and manually manage duplicate files. This repetitive task compounds across hundreds of papers in a researcher's library, creating cumulative time waste.

Score: 17.5%