Virtual Scientists V2 serves as a modular AI agent framework tailored for scientific research. It defines multiple virtual scientists—Chemist, Physicist, Biologist, and Data Scientist—each equipped with domain-specific knowledge and tool integrations. These agents utilize LangChain to orchestrate API calls to sources like Semantic Scholar, ArXiv, and web search, enabling automated literature retrieval, contextual analysis, and data extraction. Users script tasks by specifying research objectives; agents autonomously gather papers, summarize methodologies and results, propose experimental protocols, generate hypotheses, and produce structured reports. The framework supports plugins for custom tools and workflows, promoting extensibility. By automating repetitive research tasks, Virtual Scientists V2 accelerates insight generation and reduces manual effort across multidisciplinary projects.

Afforai offers a powerful AI-powered research assistant that simplifies the process of information gathering, synthesis, and analysis. By leveraging advanced natural language processing and machine learning, it allows users to delve into complex topics and niche inquiries with ease. It scours millions of sources to provide precise and reliable insights, enhancing productivity and ensuring the accuracy of your research. Whether you're a student, professional, or a researcher, Afforai transforms the way you conduct research by saving time and boosting efficiency through its intelligent capabilities.