
Industry-leading systematic review software with integrated machine learning and automated evidence synthesis.
EPPI-Reviewer is a high-performance web-based software suite developed by the EPPI-Centre at UCL for managing every stage of the systematic review process. As of 2026, it has solidified its market position as the premier tool for 'Living Systematic Reviews' through its tight integration with the Cochrane Evidence Pipeline and OpenAlex. The technical architecture revolves around a robust relational database that supports multi-user collaboration and high-volume data processing (100k+ records). Its core competitive advantage is the 'Active Learning' machine learning engine, which prioritizes screening results to reduce workload by up to 60-90%. Furthermore, the tool has integrated Large Language Model (LLM) capabilities for automated data extraction and quality assessment, allowing researchers to move from citation to synthesis with unprecedented speed. It supports diverse review types, including qualitative, quantitative, and mixed-methods research, offering specialized modules for meta-analysis and evidence gap mapping.
Uses a Naive Bayes classifier or BERT-based models to rank unscreened items based on user-inputted inclusion/exclusion patterns.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Provides a direct bridge to the R environment for meta-analysis, forest plots, and funnel plots without leaving the browser.
Automatically polls external databases like OpenAlex and PubMed for new records based on saved search strings.
Visual synthesis tool that maps studies across two dimensions (e.g., intervention vs. outcome).
LLM-powered extraction of numerical and qualitative data points from uploaded PDF files.
Sophisticated multi-user environment that handles double-blind coding and conflict resolution.
Direct synchronization with Cochrane's internal systems for high-quality evidence processing.
Manually screening 50,000+ abstracts for a medical meta-analysis.
Registry Updated:2/7/2026
Review high-probability items first
Visualizing where evidence exists for social interventions across a geographic region.
Keeping a COVID-19 review updated monthly without manual re-searching.