Rayyan
AI-powered platform for efficient systematic literature review management.
Executive Summary
Rayyan is a web-based, AI-powered platform designed to streamline systematic and literature reviews for researchers, information specialists, librarians, and students. It leverages artificial intelligence, machine learning, and natural language processing to accelerate the screening process, manage duplicates, and enhance collaborative research. The platform aims to reduce review time significantly while improving accuracy and transparency in evidence synthesis projects.
Use Cases
- Conducting systematic reviews across various disciplines.
- Performing scoping reviews and meta-analyses.
- Accelerating literature review processes for academic and clinical research.
- Facilitating collaborative research projects among multiple reviewers.
- Supporting evidence-based decision-making in healthcare and other fields.
- Training and education in systematic review methodologies.
Features
Visibility
- Centralized Review Workbench: A unified platform to manage, organize, and collaborate on systematic reviews, offering intuitive tools for tracking progress.
- Customizable Filters & Facets: Allows users to quickly find relevant studies and explore metadata like MeSH terms, authors, and keywords through flexible filtering options.
- Real-time Progress Monitoring: Enables review creators and collaborators to monitor the screening progress of the team.
- PRISMA Flow Diagram Generation: Supports the generation of PRISMA flow diagrams for transparent reporting of the review process (available with paid subscriptions).
Intelligence
- AI-Powered Screening Acceleration: Rayyan's AI streamlines the review process, significantly reducing screening time by learning from reviewer decisions.
- Advanced Duplicate Detection: Automatically identifies and removes duplicate references from imported datasets, ensuring a clean and organized review.
- 5-Star Relevance Ranking: An AI-powered system that rates the probability of an article being included in the review based on learned patterns from user decisions.
- Keyword Highlighting & Text Mining: Highlights inclusion and exclusion keywords within abstracts and titles, and uses text mining to identify relevant information, assisting manual screening.
- Prediction Classifier: Uses reviewer decisions to predict the classification of other studies, offering suggestions to guide screening.
Support
- Comprehensive Help Center: Provides extensive online resources, guides, and tutorials for users to learn and troubleshoot.
- Email Support: Users can contact the support team via email for assistance.
- Standard & Priority Support Tiers: Different levels of support are offered based on the subscription plan, including standard and priority options.
Technical Specifications
- Architecture
- Web-based SaaS application
- Deployment
- Cloud/SaaS
- Authentication
- Standard username/password, potentially OAuth for third-party integrations (not explicitly detailed)
- API Available
- No
- MCP Server
- No
Infrastructure
- AWS
- Heroku
AI/ML Stack
- NLP
- Machine Learning
- Text Mining
- Supervised Learning Algorithms
- Support Vector Machine (SVM)
Integrations
- Mendeley
- Zotero
- EndNote
- PubMed
- PRISMA
Security & Compliance
Encryption: Not explicitly detailed in public information.
Pricing
- Model
- Freemium (Free tier + Tiered subscription)
- Starting Price
- Free tier available; Student plan: $60/year. Other paid plans require contacting sales or are tiered.
- Target Customer
- Individual researchers, students, academic institutions, research teams, mid-market to enterprise research organizations.
- Contract Type
- Yearly, Quarterly (for some plans).
- Free Trial
- Yes, Indefinite (via robust free tier). (credit card required)
About Rayyan
Rayyan Systems, Inc. is a U.S.-based company that provides an AI-powered platform and mobile application for systematic literature reviews. It leverages natural language processing, artificial intelligence, and machine learning to streamline the review process, significantly reducing the time researchers spend analyzing and synthesizing scientific literature for evidence-based decision-making.