Consensus

Consensus indexes 250 million peer-reviewed research papers drawn from databases including Semantic Scholar and PubMed. The platform's homepage explicitly positions this breadth as enabling researchers to find, organise, and analyse science 10x faster than traditional methods — the foundational claim of its positioning as an AI academic search engine rather than a general web tool. Why it matters: A search corpus of this scale, limited exclusively to peer-reviewed literature, means researchers surface credible academic evidence rather than wading through web content, blog posts, or non-peer-reviewed sources.

Consensus's Deep Search feature is described on the homepage as turning days of literature review into a few minutes. The platform automatically builds comprehensive search strategies, expands key terms, identifies conflicting arguments, and explores citation graphs across its full paper corpus. This is a named, documented platform capability explicitly positioned as the primary solution to the time cost of traditional systematic literature reviews. Why it matters: For researchers conducting systematic reviews or meta-analyses, the bottleneck is typically the breadth and thoroughness of the initial search. Automating strategy expansion and citation traversal directly addresses this constraint.

Medical Mode narrows search results to approximately 50,000 clinical guidelines and 8 million articles from the top 1,000 medical journals, providing clinicians with targeted access to the highest-quality clinical evidence. This is explicitly described as a dedicated platform mode on the Consensus homepage, distinguishing it from general academic search tools that surface low-quality medical sources alongside peer-reviewed literature. Why it matters: Clinicians need to trust that evidence they find is from authoritative sources. A mode that filters to top-tier medical journals and clinical guidelines removes the risk of basing decisions on lower-quality studies.