Revolutionary AI research engine that cuts through conflicting studies to find what science actually agrees on. Get evidence-based answers from 200+ million peer-reviewed papers with confidence scores.
Search 200+ million scientific papers and get AI-powered research summaries that reveal scientific consensus — evidence-based answers for healthcare, policy, academic research, and fact-checking with confidence indicators.
Consensus operates as a specialized AI research platform that focuses specifically on identifying scientific consensus and evidence-based answers to research questions by analyzing peer-reviewed academic literature. Unlike general research tools like Google Scholar or PubMed that simply return lists of individual studies, Consensus is designed to cut through conflicting studies and contradictory findings to identify what the scientific community actually agrees on for specific topics. The platform uses advanced natural language processing to analyze millions of research papers and identify patterns in findings, methodological approaches, and conclusions across studies.
Consensus excels at providing evidence-based answers to specific questions like 'Does meditation reduce anxiety?' or 'What are the effects of remote work on productivity?' by analyzing hundreds of relevant studies and presenting a synthesized view of the scientific evidence. The platform's strength lies in its ability to weight studies based on quality, sample size, methodology, and publication venue to provide more reliable consensus views rather than simply counting studies. This sophisticated approach differentiates Consensus from traditional academic search engines that treat all studies equally regardless of their methodological rigor or sample size.
Unlike Perplexity or ChatGPT that may reference studies without systematic evaluation, Consensus employs a rigorous study quality weighting system that prioritizes research based on peer review status, methodology strength, and replication results. While Elicit focuses on extracting specific data points from papers, Consensus specializes in synthesizing findings across multiple studies to identify consensus patterns. This makes Consensus particularly valuable when you need to understand not just what individual studies say, but what the collective scientific evidence supports.
Consensus includes confidence indicators that show how strong the evidence is for particular conclusions and identifies areas where scientific opinion remains divided. The platform provides access to over 200 million peer-reviewed papers and uses the proprietary Consensus Meter to visualize agreement levels across studies. The 2026 updates introduced Study Snapshots with AI-generated paper summaries, team workspaces for collaborative research, and enhanced methodology quality weighting that provides more nuanced confidence assessments than competing platforms.
The platform is particularly valuable for professionals who need evidence-based information but lack the time or expertise to conduct comprehensive literature reviews themselves. This includes healthcare professionals, policymakers, journalists, business leaders, and students who need reliable information backed by scientific research. However, Consensus is limited to topics that have been studied in peer-reviewed literature and may not provide insights on emerging topics or questions that haven't been extensively researched. The platform also reflects the limitations and biases present in the underlying research literature, though it includes bias detection algorithms to flag potential issues.
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Consensus uniquely focuses on surfacing scientific consensus from peer-reviewed research, using its Consensus Meter to show agreement levels across studies. This approach is invaluable for evidence-based decision making and combating misinformation. The scope is narrower than general research tools, but for answering 'what does the science say?' questions, it's purpose-built and effective.
A signature visualization that shows the proportion of analyzed studies answering Yes, Possibly Yes, or No to a research question. The meter is generated by a custom-trained AI classifier that reads study findings and aligns them with the user's query, providing an at-a-glance read on the state of evidence.
An AI research assistant that generates custom written summaries answering specific research questions, with every claim grounded in cited papers. Copilot can draft contribution analyses, comparison tables, and literature review sections from scratch using the underlying corpus of 200M+ papers.
Each paper in search results includes an AI-generated snapshot showing key findings, sample size, study design (RCT, observational, meta-analysis), and population details. This allows rapid screening of dozens of papers without opening each PDF, dramatically accelerating literature triage.
Papers are tagged with rigor signals from SciScore, journal impact information, study design classifications, and citation counts. Filters let researchers narrow to high-quality study types like systematic reviews, meta-analyses, and large RCTs to surface the strongest evidence first.
AI-generated comparison tables extract structured data points across multiple papers — interventions, outcomes, sample sizes, populations — into a single sortable view. This feature mirrors workflows researchers traditionally build manually in Excel for systematic reviews, completed in seconds.
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$11.99/month (annual) or $14.99/month
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2026 updates include enhanced team workspaces for collaborative research, expanded GPT-4 Copilot capabilities with longer-form synthesis output, refined methodology quality weighting using updated SciScore signals, improved Study Snapshots with richer methodology extraction, and broader institutional integrations through the Enterprise tier.
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