WisPaper Search

WisPaper Search is a question-driven academic search tool that retrieves papers and applies AI verification and screening to surface studies worth reading. It combines Quick and Deep search modes with trend, feed and discovery panels.

WisPaper Search is an academic search interface built around a research question rather than a keyword string. Instead of assembling boolean queries and then manually filtering the results, a user describes what they want to find in plain language, for example asking for papers on AI4Science published in the last three years. The tool then locates candidate studies and applies AI verification and screening so that the returned set leans toward work that is actually relevant to the question asked. Two search modes sit at the centre of the product. Quick Search is the fast path for a single well-formed query. Deep Search is the broader option, paired on the homepage with an Agent framing, which suggests a more involved retrieval process for questions that need wider coverage. Alongside search, the interface includes Inspiration Discovery, Trends, Latest and AI Feeds sections that surface papers without a query, and a Personalize control that tunes what those feeds show. The result is a research start page rather than a bare search box. The tool fits researchers, graduate students and analysts who already know roughly what they need but lose time to screening noise. It is most useful at the front of a literature review, when the task is narrowing a large body of publications down to a shortlist worth reading in full. It is a discovery and screening layer, not a reference manager or a PDF reader, so it complements a citation tool rather than replacing one. Teams evaluating it should test whether the verification step matches their field's standards, since relevance judgements vary a great deal between disciplines. The homepage gives no pricing, integration or support detail, so budget and workflow questions need answers from the vendor directly.