Rayyan: Why Structured Data Extraction & Evidence Intelligence Are Becoming Non‑Negotiable in 2026

Overview: How Rayyan’s AI‑Driven Structured Data Extraction & Evidence Intelligence Platform Transforms Evidence & Regulatory Workflows

Rayyan is an AI‑powered platform for Evidence and Regulatory work that supports Structured Data Extraction & Evidence Intelligence by managing the full workflow from literature screening through to structured data export. It addresses the bottleneck of screening and extracting data from large volumes of studies, where traditional manual approaches to identifying relevant records, resolving reviewer conflicts, and standardising extracted variables can be slow and resource‑intensive. Rayyan applies machine learning and natural language processing to prioritise likely‑relevant articles, suggest inclusion decisions, and streamline coding of key study fields, while maintaining reviewer blinding and conflict resolution steps that preserve methodological rigour.

Within this category, Rayyan provides a configurable data extraction environment where teams can define custom questions and answer types, capture structured study characteristics and outcomes, and export harmonised datasets for meta‑analysis or further evidence intelligence work. Integrated PDF viewing, progress tracking, and multi‑reviewer workflows reduce context switching and make it easier to manage large review projects to completion. By combining AI‑assisted screening with structured extraction and collaboration tools, Rayyan can shorten evidence synthesis timelines and reduce administrative overhead while supporting more consistent, transparent data capture across complex evidence programmes.

Last checked on May 19, 2026: Rayyan remains an active AI‑powered evidence review platform, with recent releases focusing on AI agents for screening and data extraction, richer extraction tables, and performance improvements to its web and mobile apps.

What is Rayyan?

Rayyan is an AI-powered platform for managing systematic and other evidence reviews, with features for screening, structured data extraction, and evidence organisation within the Evidence and Regulatory, Structured Data Extraction & Evidence Intelligence category. It is primarily used by researchers and evidence teams who need to filter large literature sets, apply inclusion and exclusion criteria, and extract structured study data into configurable tables for meta-analysis and other evidence syntheses. Rayyan is differentiated by its machine learning–assisted screening (including relevance ranking and semi-automated classification), integrated data extraction environment, and support for collaborative, blinded multi-reviewer workflows that maintain auditable links from decisions back to source records.

Why Do Leading Healthcare Teams Trust Rayyan?

• Rayyan originated as an AI-assisted systematic review tool developed at the Qatar Computing Research Institute and is now operated by Rayyan Systems Inc., a US-based startup created through a partnership to scale the platform for global scientific and biomedical users.

• A strategic partnership with Thera-Business provides combined offerings for pharmacovigilance, clinical evaluation reports, health technology assessments, and other regulated evidence activities, positioning Rayyan within end-to-end evidence services for regulated biomedical and healthcare entities.

• Rayyan is described as an AI-assisted collaboration platform for systematic literature reviews, with published evaluations (e.g., ISPOR presentations) assessing its artificial intelligence–based screening capabilities in systematic review workflows.

• Academic and professional organisations, including the London School of Hygiene & Tropical Medicine, have hosted webinars and training sessions around Rayyan as an “intelligent web and mobile application for systematic literature reviews,” signalling acceptance within the evidence synthesis community.

• Rayyan’s public materials emphasise a human-in-the-loop approach where AI supports, but does not replace, expert judgement in screening and evidence assessment, which aligns with emerging expectations for responsible use of AI in evidence and regulatory contexts.

• The company presents itself as a SaaS platform with web and mobile access and has been in continuous operation for several years, with no public reports of acquisitions, rebrands, or major corporate disruptions, suggesting organisational stability