AI Research

Consensus

An AI-powered academic search engine that synthesizes findings across peer-reviewed papers and visually summarizes whether the evidence supports a given claim.

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What it does

Consensus is an academic search engine that lets users ask plain-language research questions and get back a synthesis of what peer-reviewed literature says, anchored by its signature Consensus Meter — a visualization based on the top-ranked papers on that question. It draws on a large index of scientific papers and offers a specialized Medical Mode for clinical guideline-backed queries, making it well suited to fast, evidence-based research questions rather than deep systematic-review data extraction.

Ideal users

  • Students and academics doing evidence-based literature searches
  • Clinicians and medical researchers via its Medical Mode
  • Journalists or writers fact-checking scientific claims
  • Anyone who wants a quick read on what the evidence says on a research question

Who should avoid it

  • You need large-scale systematic-review screening and extraction across thousands of papers — Elicit is stronger here
  • You need general, non-academic web search
  • You need to go beyond a high-level synthesis into deep methodological critique yourself

Key features

  • Consensus Meter — a visual yes/no/possibly synthesis across the top papers on a question
  • Deep Search that automates search strategy across up to 1,000 papers
  • Medical Mode filtering to roughly 50,000 clinical guidelines plus 8 million articles from top medical journals
  • Study Snapshots — AI-generated summaries of individual papers
  • An index of 220M+ papers with 170+ university library partnerships

Pros / Cons

Pros

  • Consensus Meter gives a fast, intuitive read on scientific agreement for a claim
  • Medical Mode is a strong fit for clinicians needing guideline-backed answers
  • Large, reputable academic corpus
  • Usable free tier for casual academic lookups

Cons

  • Consensus Meter simplifies nuanced findings into a simplified view — real disagreement or methodological caveats can get flattened
  • Less suited than Elicit for large-scale systematic-review data extraction
  • Deep Search and Pro-tier pricing details vary across sources
  • Not a general web search tool

Pricing

Free — ~$12/month (Pro, billed annually)

Pro is $12/month billed annually ($144/year), or $20/month billed monthly. A higher Deep tier is $45/month and adds around 200 Deep Searches/month on top of Pro. Student (~40%) and clinician (~25%) discounts are available.

Typical workflows

  • A user types a yes/no research question and gets a Consensus Meter summarizing the balance of evidence across top papers, plus links and snapshots of the underlying studies.
  • A clinician switches to Medical Mode to get guideline-backed answers filtered to trusted clinical sources rather than the full general academic corpus.

Integrations

  • API access (by application)
  • University library partnerships (170+)

Privacy & security notes

The Consensus Meter is a simplified visualization of a complex evidence base — always read the underlying Study Snapshots and, for important decisions, the original papers, since a summarized rating can mask methodological weaknesses or conflicting study designs.

Frequently asked questions

What is the Consensus Meter?

A visual summary of how the top-ranked papers on a topic answer a specific research question, weighted by citation count and study design.

Is Consensus good for medical research specifically?

Yes — its Medical Mode filters to clinical guidelines and top medical-journal articles for evidence-based clinical questions.

How is Consensus different from Elicit?

Consensus emphasizes a fast, visual synthesis of what the evidence says, while Elicit is built more for structured, large-scale data extraction and systematic review workflows.

Can I trust the Consensus Meter as a final answer?

No — treat it as a starting point; the underlying papers and their methodology should still be reviewed for anything used in serious research or publication.

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