Rayyan

What is Rayyan?

Rayyan is an AI-powered systematic review and literature review platform designed for researchers, academics, and healthcare professionals. It helps teams discover, screen, organize, and analyze research papers more efficiently. Rayyan supports study screening, duplicate detection, collaboration, inclusion and exclusion decisions, and AI-assisted research workflows. Its features are useful for systematic reviews, evidence-based research, and academic literature management, helping researchers reduce manual work while keeping the review process organized, transparent, and collaborative.

Originally incubated at the Qatar Computing Research Institute (QCRI) by Mourad Ouzzani, Hossam Hammady, Zbys Fedorowicz, and Ahmed Elmagarmid, Rayyan has grown into an essential standard in global research, trusted by over 500,000 researchers across 180+ countries. The platform pairs AI-driven relevance prediction rankings with deterministic systematic review workflows. Rayyan supports automated duplicate detection and resolution, customizable 15+ facet workbench filters, double-blinded multi-reviewer screening, PRISMA flow diagram generation, structured PICO data extraction, Risk of Bias (RoB) evaluation, and ResearchPilot AI institutional literature pipelines.

• Origin / Leadership: Incubated at QCRI; operated by Rayyan Systems Inc. (Cambridge, MA, USA & Global; founded in 2016)
• Research Standard: Widely cited across thousands of published systematic reviews, meta-analyses, and scoping reviews indexed in PubMed, Cochrane, and Nature
• Evolution / Launch: Evolved from an early web screening tool into an end-to-end evidence synthesis ecosystem featuring native iOS/Android offline screening apps, automated PRISMA diagrams, AI PICO extraction, Risk of Bias (RoB) modules, and institutional ResearchPilot AI through 2024–2026

Use Cases:

• Screening thousands of titles and abstracts rapidly for systematic literature reviews, scoping reviews, and clinical practice guidelines
• Enforcing double-blind screening protocols between multiple independent co-reviewers to eliminate evaluation bias
• Detecting and auto-resolving duplicate citations across PubMed, Embase, Cochrane, Scopus, and Web of Science reference exports
• Extracting structured PICO (Population, Intervention, Comparison, Outcome) data elements and generating publication-ready PRISMA flowcharts

Technology:

• Active learning prediction engine calculating five-star relevance likelihood scores as reviewers make inclusion decisions
• Systematic Auto-Resolver algorithm identifying exact and near-match reference duplicates across multi-database search imports
• Blinded collaborative architecture preventing team members from viewing each other's inclusion labels until blinding is formally turned off

Target Users:

• Biomedical, public health, and clinical researchers conducting formal Cochrane or Campbell systematic reviews
• Academic professors, postdoctoral fellows, and PhD candidates writing dissertations and scoping literature reviews
• Medical librarians and research informationists managing institutional literature search pipelines
• Content creators using writing tools to draft evidence-based medical summaries, clinical literature overviews, and healthcare research guides

Corporate Entity: Operates as Rayyan Systems Inc. (Cambridge, MA, USA & Global)

Key features of Rayyan

Rayyan's key features are

• AI Relevance Predictions: Active learning model learns from your initial inclusion/exclusion decisions and predicts relevance scores (1 to 5 stars) across remaining records.
• Blinded Multi-Reviewer Collaboration: Maintain rigorous methodological standards with blind screening modes, custom inclusion/exclusion labels, and conflict resolution dashboards.
• Systematic Auto-Resolver (Deduplication): Industry-leading duplicate detection engine identifies matching citations and resolves duplicates in bulk.
• Automated PRISMA Flow Diagrams: Generates standardized PRISMA 2020 flowcharts documenting records identified, screened, excluded, and included with one click.
• PICO & Structured Data Extraction: Leverages AI to parse, extract, and categorize Population, Intervention, Comparison, and Outcome frameworks into structured tables.
• Risk of Bias (RoB) Assessment: Standardized modules allowing review teams to assess methodological study bias with consistency and transparency.
• Mobile Screening App (iOS & Android): Dedicated mobile apps with gesture-based swipe controls and offline caching for screening studies anywhere.
• ResearchPilot AI & Enterprise Console: Scalable enterprise platform for universities and hospitals to manage team seats, audit trails, and institutional reviews.

Rayyan Pricing

Rayyan operates on an accessible freemium model offering a free review tier alongside individual Essential and Advanced subscriptions, and customized institutional licenses with ResearchPilot AI.

Free Plan:

• $0 / Free forever
• Includes up to 3 active reviews, invite 2 free reviewers, 1 sample subset, industry-leading duplicate detection, AI relevance predictions, 15+ workbench facets, and limited mobile app access

Essential Plan:

• Annual Billing: $4.99 / seat / month ($59.88 billed annually)
• Quarterly Billing: $8.33 / month ($24.99 billed quarterly)
• Includes all Free features plus automated PRISMA flow diagrams, invite up to 5 free reviewers, systematic auto-resolve duplicates, unlimited mobile app access, bulk actions, and programmable keyboard shortcuts

Advanced Plan (Most Popular):

• Annual Billing: $8.33 / seat / month ($99.99 billed annually – best value)
• Quarterly Billing: $13.33 / month ($39.99 billed quarterly)
• Includes all Essential features plus up to 9 active reviews, invite up to 10 free reviewers, unlimited sampling, AI-driven PICO data extraction, and priority support

Institutional / Enterprise (ResearchPilot AI):

• Starts from $41.67 / license / month billed annually (starting at 5 licenses / $2,500.00 / year) or custom campus-wide agreements
• Includes full platform access with ResearchPilot AI, 50 to unlimited org-wide reviews, invite up to 250 reviewers, team admin consoles, API/Python SDK access, and dedicated onboarding

Disclaimer: Prices are listed in USD and exclude local taxes. Subscriptions renew automatically unless canceled before the renewal date. Free accounts can be created with zero credit card commitment. Visit rayyan.ai/pricing for active plans.

Who is using Rayyan?

Rayyan is designed for researchers, academic institutions, and healthcare teams, including

• Systematic Review Teams & Epidemiologists: Screening tens of thousands of biomedical literature references under strict blinded methodology
• Medical & Life Sciences Students: Conducting graduate dissertations, capstone scoping reviews, and clinical meta-analyses
• Academic Faculty & Research Labs: Dividing screening workloads, resolving inclusion conflicts, and generating PRISMA charts
• Hospital Research Committees & Librarians: Standardizing institutional literature evaluations and managing team seats across departments
• Content Creators: Using writing tools to draft evidence-based medical summaries, clinical literature overviews, and healthcare research guides
• Pharmaceutical & MedTech R&D Teams: Tracking safety signals, regulatory literature reviews, and medical device clinical evaluations

Best Rayyan Alternatives

Some of the strongest Rayyan alternatives include

• Covidence
• DistillerSR
• EvidenceHunt 
• Elicit 
• EPPI-Reviewer
• Sysrev 

Pros and Cons of Rayyan

Pros

• Generous free plan allows up to 3 active reviews and collaborative screening at zero cost
• Active learning AI prediction engine learns reviewer patterns to prioritize high-relevance studies first
• Robust blinding mechanisms ensure methodological rigor and compliance with Cochrane standards
• Native mobile apps with offline synchronization enable screening on smartphones and tablets during commutes
• Significantly more affordable annual plans ($4.99–$8.33/mo) compared to expensive alternatives like Covidence or DistillerSR

Cons

• Automated PRISMA diagram exports and duplicate auto-resolving require at least an Essential subscription ($4.99/mo)
• Full-text PDF screening and advanced data extraction are less automated than specialized extraction engines like DistillerSR
• Free plan limits active reviews to 3 and collaborators to 2 named reviewers
• Requires importing standard reference citation files (RIS, BibTeX, EndNote) rather than running built-in live database discovery internally

Why Choose Rayyan?

Rayyan is the premier choice for research teams, academic institutions, and healthcare professionals who need an accessible, methodologically rigorous systematic review platform that combines blinded screening, active learning AI rankings, deduplication, and mobile access at a fraction of the cost of legacy tools.

• Screen titles and abstracts up to 50% faster using active learning AI relevance predictions
• Enforce double-blind screening to eliminate bias and maintain Cochrane compliance
• Detect and auto-resolve duplicate citations across multiple database imports
• Generate standardized PRISMA 2020 flow diagrams ready for manuscript publication
• Screen on the go using native iOS and Android mobile apps with offline mode

Rayyan vs. Competitors

The main difference between Rayyan, Covidence, DistillerSR, and EvidenceHunt is that Rayyan focuses on fast, collaborative title and abstract screening, deduplication, and blinded workflows with a generous free plan and accessible $4.99–$8.33/mo subscriptions, whereas Covidence charges substantially higher individual/institutional fees (~$240+/yr), DistillerSR focuses on enterprise regulatory compliance, and EvidenceHunt specializes in point-of-care clinical literature search and hospital protocol connections. Rayyan stands out for its high screening velocity, user-friendly mobile apps, and unmatched affordability for academic researchers.

How do we rate Rayyan?

Rayyan Review

Rayyan has earned its reputation as the gold standard for title and abstract screening in academic and clinical evidence synthesis. For researchers managing large-scale systematic reviews, manually evaluating tens of thousands of citations in spreadsheets is prone to human error and methodological bias. Rayyan addresses this challenge with a purpose-built workspace: active learning algorithms observe user inclusion decisions and rank remaining citations by relevance, while blind-screening tools ensure co-reviewers evaluate studies independently until conflicts are ready for discussion. With its accessible free tier, mobile apps with offline caching, and automated PRISMA diagrams, Rayyan remains an indispensable platform for evidence synthesis.

Conclusion

Rayyan is an established systematic literature review workbench that streamlines evidence synthesis for researchers and healthcare professionals worldwide. By combining active learning AI relevance predictions, blinded collaboration, auto-deduplication, PRISMA flowchart generation, and cross-platform mobile screening, it transforms time-consuming literature reviews into an efficient, collaborative process. While life sciences organizations conducting complex regulatory audits may consider DistillerSR and clinicians seeking point-of-care guidance will turn to EvidenceHunt, Rayyan’s methodological rigor, screening velocity, and accessible pricing make it an essential research tool.