Consensus
Consensus is an AI academic search engine that answers research questions with cited evidence from peer-reviewed literature.
If a citation decides whether your work holds up, Consensus is worth the trial. The Consensus Meter gives you a defensible read on a contested yes-or-no question in about a minute, and Deep Search handles broader sweeps with citation-graph tracing. Just don't buy it expecting a finished systematic review or help with non-STEM literature, because you won't get either.
Verified 19m ago · liveness 88/100 · cite: rightaichoice.com/tools/consensus
- Graduate students scoping a literature review who need cited answers fast
- Clinicians checking treatment effectiveness against top medical journals and guidelines
- Researchers entering a new field who want a quick read on the state of the evidence
- Institutional and library buyers provisioning research tools to faculty and students
- Deep single-paper reading or analysis inside the platform
- Non-STEM fields like philosophy, arts or literature where coverage is sparse
- Questions that don't need citations or peer-reviewed sources
We scan live Reddit threads, YouTube comments, X posts, G2 reviews and other communities — and hand you an honest verdict in under a minute.
- Honest verdict, not marketing
- Real pros & cons from real users
- Attributed quotes with receipts
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Skip Consensus if your question is in the humanities or needs deep single-paper interrogation rather than a cited synthesis of the literature.
Unlimited Deep Search runs are a Premium feature at $10.99/mo — the free tier limits how many you get, so heavy users hit the cap quickly.
The Free tier covers the paper index, cited answers, and the Consensus Meter, which is enough for a student fact-checking a claim. Premium at $10.99/mo (annual pricing published on the pricing page) is the tier for anyone running Deep Search regularly or asking clinical questions. Team and Enterprise are custom-quoted for departments and libraries — cheaper per seat than buying individual Premium seats at scale, but you trade self-serve signup for a procurement conversation.
In short
Consensus — Consensus is an AI academic search engine that answers research questions with cited evidence from peer-reviewed literature. Best for Graduate students scoping a literature review who need cited answers fast, Clinicians checking treatment effectiveness against top medical journals and guidelines, Researchers entering a new field who want a quick read on the state of the evidence. Free to start; paid plans from $10.99/mo.
What's new in Consensus
Checked 8 days agoAcross the latest 1 update: 1 news mention.
What people actually say about Consensus — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
73 mentions across 4 sources (Hacker News, Product Hunt, Stack Overflow, Lemmy) · researched Aug 18, 2026.
Average across the 4 sources that answered — each source counts once, not each post.
- +Cites sources for every AI-generated answer, boosting trust.
- +Consensus Meter visualizes agreement across studies clearly.
- +Filters by study type, sample size, and journal tier.
- +Medical Mode restricts results to top medical journals.
- +Chrome extension integrates with PubMed for quick access.
- −Coverage outside STEM and medicine is very limited.
- −Many results are abstract-only, not full text.
- −Free tier has limited searches per day.
- −Advanced features like CSV export require premium.
- −Not a substitute for single-paper deep analysis.
- • Premium required for advanced filters and CSV export
- • Third-party database access (Scopus) may need institutional subscription
Viability Score
How well maintained and how widely used is Consensus? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- AI answers with citations from a 250M+ peer-reviewed paper index
- Consensus Meter shows how much evidence agrees on a yes-or-no question
- Deep Search automates literature review and expands key terms
- Deep Search identifies conflicting arguments across the literature
- Deep Search explores the citation graph to trace related studies
- Medical mode filters to about 50,000 clinical guidelines and 8M articles
- Medical mode draws on the top 1,000 medical journals
- Natural-language filters auto-apply timeframes, populations and study designs
- Filter by study type such as RCT, meta-analysis or systematic review
- Skills for quick TL;DR summaries and research-gap identification
- Build a comparison table between two research approaches
- Licensed full-text content from leading publishers
- Save and organize research collections
- CSV export of search results
- Chrome extension for searching peer-reviewed literature from the web
About Consensus
Consensus is an AI academic search engine built for people who have to defend their sources. Type a plain-language research question and it returns a synthesis of what the published literature says, with citations attached to the claims. The index covers 250M+ research papers, including licensed full-text content from leading publishers, and the vendor reports 10 million researchers, students and clinicians working in it day to day. The product splits into different jobs rather than one search box. The Consensus Meter takes a yes-or-no question and instantly shows how much of the evidence agrees or disagrees, which is the fastest way I know to read a contested topic. Deep Search automates literature review by building a search strategy, expanding key terms, identifying conflicting arguments and exploring the citation graph. Skills let you pull the specific output you want: a quick TL;DR, research-gap identification, or a straight yes/no answer. On the clinical side, Medical mode narrows results to roughly 50,000 clinical guidelines and 8M articles drawn from the top 1,000 medical journals. Filters can be written in natural language, so prompts like "large human studies (n > 1,000) on intermittent fasting" apply the right study-design and population constraints automatically. Results save into collections, export to CSV, and can be pulled from the web via a Chrome extension. Adoption leans institutional: over 170 university libraries partner with Consensus to provision access for students and faculty. Position it between raw indexes like PubMed or Google Scholar and full systematic-review software. It is a synthesis layer over the evidence, not a replacement for reading the papers.
Behind the Verdict
Where Consensus earns its keep is speed on questions with a shape. Ask whether SGLT2 inhibitors reduce all-cause mortality in type 2 diabetes and the Consensus Meter answers visually in under a minute, then lets you drill into the underlying studies. During a dissertation scoping phase or a clinical check before a consult, that's genuinely a few hours saved per week. Deep Search is the more ambitious half. It doesn't just retrieve; it builds the search strategy, expands key terms, flags where the literature disagrees and walks the citation graph sideways into adjacent work. For entering a new field, that's a better starting map than a Scholar results list. Pick Consensus when your question is empirical, the answer should be citable, and you can live with an extraction-and-synthesis layer rather than a document you submit. Students, clinicians and researchers onboarding into unfamiliar territory get the most out of it. Pass when you need to interrogate a single paper closely, when your field is philosophy, arts or literature where the indexed coverage thins out, or when the deliverable is prose rather than sources. Teams that need end-to-end systematic-review workflow — protocol registration, dual screening, PRISMA reporting — will outgrow it. The closest alternative is Elicit for structured extraction and table-building from papers; general assistants handle the write-up but are weaker at staying inside a peer-reviewed corpus. In practice, Consensus is the front of the funnel, not the whole pipeline. Budget time to actually open the papers it cites: the meter tells you the balance of evidence, not whether the studies were any good.
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Real-world workflow fit
Concrete scenarios for the personas Consensus actually fits — and what changes day-one when you adopt it.
You have a thesis topic and need a defensible starting set of papers. You type your research question into Consensus, use natural-language filters to specify 'systematic reviews from the past 5 years', and read the cited synthesis. Then you run Deep Search to expand key terms and surface conflicting arguments you hadn't considered.
Outcome: You leave with a set of papers, a map of where the literature disagrees, and cited summaries you can hand to your advisor — instead of a week of database screening.
A patient asks about a treatment you don't prescribe often. You switch on Medical mode, which narrows retrieval to roughly 50,000 clinical guidelines and 8M articles from the top 1,000 medical journals, and ask a focused question.
Outcome: You get guideline-grounded answers with citations to the top-tier medical literature, filtered down from the general corpus, in the time it takes to open a chart.
You're pivoting and need to know where the field stands. You ask a yes-or-no question and the Consensus Meter shows how much of the published evidence agrees. You follow up with Deep Search to walk the citation graph outward from the key papers.
Outcome: You get a visual read on the state of the evidence plus the citation trail to the foundational work, which is faster than starting from scratch in PubMed and Google Scholar.
Use Cases
- Verify scientific consensus before citing a claim in a paper
- Find supporting or refuting studies for a grant proposal
- Generate literature summaries for assignments
- Check the strength of evidence behind a health claim
- Exploratory research on a field you're entering
- Check first-line and second-line treatment options for a clinical question
- Compare randomized versus observational evidence on the same intervention
Models Under the Hood
as of 2026-10-08
Limitations
- AI summaries may miss nuances, and the free tier caps Deep Search runs.
- Coverage varies by field — the 250M+ paper index is deepest in biomedicine and the health sciences, so non-STEM questions may return thin results.
- Full-text access depends on publisher licensing and is not uniform across the corpus.
- Consensus is a synthesis layer over the evidence, so it gives you a defensible starting set of papers, not a finished manuscript — you still read the papers and check the methods yourself.
- For deep single-paper analysis or an end-to-end PRISMA screening workflow, you will need a different tool alongside it.
as of 2026-09-30
Verification history
We have re-verified Consensus 99 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 99 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Consensus tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Free
$0/mo
Ideal for
Students and researchers who need the Consensus Meter and cited answers but only run Deep Search occasionally.
What this tier adds
Starting tier: 220M+ peer-reviewed paper index, unlimited cited answers, and the Consensus Meter, with limited Deep Search runs.
Premium
$10.99/mo
Ideal for
Clinicians and graduate students who run Deep Search regularly or need guideline-grounded clinical answers.
What this tier adds
Adds unlimited Deep Search with expanded search strategy, citation-graph exploration, Medical mode, CSV export, and research collections.
Team
Custom
Ideal for
Research groups and departments that need shared collections and centralized billing rather than individual seats.
What this tier adds
Adds seats for research groups, shared research collections, centralized billing, and volume pricing.
Enterprise
Custom
Ideal for
Universities, health systems, and libraries provisioning access across an institution.
What this tier adds
Adds institutional access, library partnership provisioning, licensed full-text publisher content, and admin controls with usage reporting.
Where the pricing makes sense
The company stage and team size where Consensus's pricing actually pencils out — and where peers do it cheaper.
The Free tier covers the paper index, cited answers, and the Consensus Meter, which is enough for a student fact-checking a claim. Premium at $10.99/mo (annual pricing published on the pricing page) is the tier for anyone running Deep Search regularly or asking clinical questions. Team and Enterprise are custom-quoted for departments and libraries — cheaper per seat than buying individual Premium seats at scale, but you trade self-serve signup for a procurement conversation.
Setup time & first value
How long it actually takes to get something useful out of Consensus — broken out by persona, not the marketing-page minute.
Individual researchers: sign up and run a first cited question in under five minutes — no setup, no configuration. Students and clinicians: 10-15 minutes to learn the natural-language filter syntax and the study-type filters, which is where most of the leverage is. Institutional and library buyers: expect a procurement cycle rather than a setup time, since Enterprise provisioning and licensed
Switching to or from Consensus
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From Google Scholar: run the same question in Consensus first to get a cited synthesis, then use the citation graph to reach the papers Scholar would have surfaced.
- →From PubMed: import the habit of study-type filtering, but write the design constraint directly into the prompt and let Consensus apply it.
- →From a general-purpose chatbot: replace unverifiable answers with cited ones — the Consensus Meter and Deep Search give you the citation trail a chatbot omits.
- →From manual literature screening: use Deep Search to build the search strategy and surface conflicting arguments before you start reading.
- ↗To a full systematic-review platform: export your collections to CSV and take the candidate set into your PRISMA screening workflow.
- ↗To a reference manager: use CSV export to bring saved papers into Zotero, Mendeley, or EndNote.
- ↗To a general-purpose chatbot: keep Consensus for cited evidence and use the chatbot only for drafting or reformulating once you have your sources.
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Consensus”, and we withheld 5: 5 could not be judged, because “Consensus” is a single word that other videos use for other things. Showing the 1 we can prove is about Consensus.
Tools that pair well with Consensus
Common stack mates teams adopt alongside Consensus, with the specific reason each pairing earns its keep.
SciSpace
SciSpace is an end-to-end academic research platform for finding, reading, extracting, and writing up scientific literature with AI help.
Elicit
Semantic search over 138M papers and 545K clinical trials, with a cited research agent that writes evidence reviews you can defend.
Metaso AI
Chinese-language search engine that returns cited, synthesized answers instead of link lists.
Featured Head-to-Head Comparisons
Consensus vs Semantic Scholar
If you need synthesized, cited answers for a research question—especially in medicine or STEM—Consensus is the evidence-filtering workhorse. But if your priority is unrestricted, free search across a larger corpus with developer-friendly API access and quick TLDR summaries, Semantic Scholar is the no-brainer. Choose Consensus for depth and consensus visualization; choose Semantic Scholar for breadth and zero cost.
Consensus vs Litmaps
If you're mapping a research landscape and tracking how papers relate over time, Litmaps is the clear winner — its visual, citation-based approach is unmatched. But if you need quick, evidence-backed answers to clinical or STEM questions, Consensus is your tool. Choose based on whether you prioritize seeing the whole field or zeroing in on specific consensus.
Consensus vs Scispace
If your core need is quickly synthesizing evidence from millions of papers—especially in STEM and medicine—Consensus is the sharper tool with its Consensus Meter and medical filters. If you want an all-in-one workspace to read, write, and cite with AI assistance, SciSpace offers a broader feature set, including PDF chat and citation generation. Choose based on whether you lean toward discovery or drafting.
Consensus vs Perplexity
If your work lives in peer-reviewed research — literature reviews, evidence-based medicine, or diving into a new STEM field — Consensus is the clear pick with PubMed/Scopus integration, study-type filters, and consensus visualization. If you need current, broad web answers with citations for everyday or professional research, Perplexity’s real-time search and file uploads are more versatile. Choose based on your primary source domain: academic literature vs. live web.
Alternatives to Consensus
View allSciSpace
SciSpace is an end-to-end academic research platform for finding, reading, extracting, and writing up scientific literature with AI help.
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