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SciWeave is an AI-powered research assistant designed to answer scientific questions using peer-reviewed and open-access research literature. Rather than returning lists of search results, it synthesizes findings from across the scientific corpus into clear, structured responses that are explicitly grounded in cited sources. Each answer links back to the underlying publications, allowing users to verify claims, review original studies, and reuse references in their own work. Users ask questions in natural language and receive responses derived from relevant research papers, with source metadata such as authors, journals, publication dates, and identifiers made visible. The tool is applicable across a wide range of use cases, including rapid familiarization with new research areas, literature review support, verification of scientific claims, and preparation for writing, grant proposals, or peer review. It is particularly useful in interdisciplinary contexts where relevant evidence may be distributed across fields with different terminology and conventions. For students, SciWeave helps bridge the gap between introductory materials and primary literature. It provides accessible, evidence-based answers while maintaining direct links to original sources, supporting learning, critical reading, and correct citation practices. For scientists and researchers, it reduces time spent on manual search and triage by presenting synthesized evidence that can be quickly assessed and traced back to the literature. SciWeave addresses a key limitation of existing tools. Traditional search engines require users to manually interpret and combine results, while general-purpose AI systems often lack reliable sourcing. By combining conversational synthesis with explicit citations, SciWeave offers a practical way to access scientific knowledge that is both efficient and suitable for academic and professional use.


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