AnswerThis

AnswerThis searches over 300 million papers, checks each claim against its source and helps draft cited literature reviews and systematic reviews in one workspace. Built for students, clinicians and research teams, with a free start.

AnswerThis is a web-based research assistant aimed at people who have to read, cite and defend a body of scientific literature. A user types a question or pastes a protocol or draft, and the system searches a database of more than 300 million papers, trials and PDFs, judging each one for relevance. Results can be narrowed by database, journal quality, date and study type, and every answer carries clickable citations that jump to the exact passage in the source. The pitch rests on verification. According to the vendor, each statement is checked against the paper it came from before it is shown, and anything that cannot be traced to a real paper is dropped rather than guessed. That targets the most common complaint about general chat assistants: invented or misquoted references. Around that core sit a personal library with collections, tags, highlights and full-text search, with sync from Zotero and Mendeley, plus a document editor with an AI writer that cites from the library in one click, checks for AI-generated text or plagiarism, and switches between more than 2,000 citation styles. Teams are covered too. Co-authors share a workspace with roles and permissions set by the owner, and a systematic review mode handles screening, extraction, meta analysis and grading with every change logged, aimed at PRISMA and Cochrane compliance. An enterprise tier adds SSO/SAML and institutional system integrations, and the company states that user data is never used to train models. Separate pages describe a literature review generator, a research gap finder, a citation map, bibliometric analysis, an essay writer and an MCP connection. Among alternatives, AnswerThis sits closer to specialised academic tools than to general chatbots. Its breadth, from first search to a submission-ready document, suits graduate students, clinicians and consultants who would otherwise juggle several apps, though accuracy claims come from the vendor and still deserve a manual spot check before anything is submitted.