Rayyan is a free web and mobile app designed to expedite the initial screening of abstracts and titles in systematic reviews. The app aims to automate the process while maintaining high usability. During beta testing, Rayyan was evaluated using two Cochrane reviews with 273 and 1030 records, respectively. The app's features, including its prediction model, were tested and refined based on user feedback. User surveys reported an average time savings of 40% compared to other tools, with 34% of respondents reporting more than 50% time savings. Key features highlighted by users include screening and labeling studies, and collaborating on reviews. As of November 2016, Rayyan has over 2000 users from more than 60 countries, conducting hundreds of reviews with a total of over 1.6 million citations. The app's architecture is cloud-based, allowing for scalability and cost-effectiveness. Rayyan's prediction model uses a support vector machine classifier to suggest studies for screening, reducing the workload for reviewers. Future developments aim to enhance duplicate detection, risk of bias assessment, automatic data extraction, and integration with other software platforms.Rayyan is a free web and mobile app designed to expedite the initial screening of abstracts and titles in systematic reviews. The app aims to automate the process while maintaining high usability. During beta testing, Rayyan was evaluated using two Cochrane reviews with 273 and 1030 records, respectively. The app's features, including its prediction model, were tested and refined based on user feedback. User surveys reported an average time savings of 40% compared to other tools, with 34% of respondents reporting more than 50% time savings. Key features highlighted by users include screening and labeling studies, and collaborating on reviews. As of November 2016, Rayyan has over 2000 users from more than 60 countries, conducting hundreds of reviews with a total of over 1.6 million citations. The app's architecture is cloud-based, allowing for scalability and cost-effectiveness. Rayyan's prediction model uses a support vector machine classifier to suggest studies for screening, reducing the workload for reviewers. Future developments aim to enhance duplicate detection, risk of bias assessment, automatic data extraction, and integration with other software platforms.