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Our Methodology

Our Goal

Our mission is to make research more accessible by simplifying access to scientific information and demonstrating that AI can bridge the gap between complex topics and a wider audience.

Agentic AI for Reports Generation

To streamline the process of gathering and synthesising research data, we use an agent-driven pipeline:

  • A large language model is prompted to retrieve comprehensive information on research efforts aimed at curing rare diseases.
  • The agent has access to a web search tool and can parse the results to extract relevant insights.
  • The website is open source; the generator pipeline can target any OpenAI-compatible model, including a local one.

Open-Source

This project is entirely open source. UpToCure GitHub Repository.

Built thanks to numerous open-source projects, with a special emphasis on the Open Deep Research framework.

Limitations

  • Risk of hallucinations: LLMs can occasionally produce inaccurate or fabricated information. Always verify with the cited sources.
  • Recent research gaps: very recent scientific developments may not yet be referenced on the web.
  • Translation accuracy: reports are initially generated in English and then translated to other languages.