Consensus is a search tool built for academic and scientific literature. You ask a question in plain language and it pulls relevant peer-reviewed papers, summarizes what they found, and links directly back to the sources so you can check the claims yourself. It draws on a corpus cited at over 220 million papers.
The product has changed a lot since its early days. It launched around the idea of a "consensus meter" that showed the percentage of studies agreeing with a claim, and while that feature still exists, it is no longer the headline. The 2026 version (no numbered release) is organized around Deep Search and a Research Agent.
Deep Search breaks your question into sub-questions, runs up to roughly 20 targeted searches, and synthesizes across as many as 50 papers, with a wide-coverage mode that can scan up to about 1,000. The Research Agent handles multi-step research questions, Medical Mode restricts sources to clinical guidelines and top medical journals, and an improved MCP lets you use Consensus inside ChatGPT, Codex, Claude, and Claude Code.
Pricing is freemium. Free ($0) gives you basic Quick Search, abstract summaries, limited Pro messages, and about 3 Deep Searches a month. Student is $9/mo with .edu/.ac verification and up to ~40% off annual. Pro is $10/mo for unlimited Pro search, a larger Deep Search allotment, Study Snapshots, and full export (~33% off annual). A higher Deep tier is reported at $45/user/mo with around 200 Deep Searches a month and unlimited snapshots.
The limits are worth knowing. Free Deep Search is capped tightly, so heavy users will hit the paywall quickly. Coverage skews toward what is indexed and abstract-level for some records, and like any AI summarizer it can flatten nuance, so you still need to read the primary sources for anything high-stakes. Note also that an unrelated sales-demo product at goconsensus.com shares the name and costs $600-$1,250/mo; it is not this tool.
It suits researchers, students, clinicians, and analysts who want grounded, citable answers from the literature and are comfortable verifying against the originals rather than trusting a summary at face value.
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