Inciteful
Accelerate academic research through intelligent citation graph analysis.
The premier comprehensive systematic review software for evidence-based healthcare research.
JBI SUMARI (System for the Unified Management, Assessment and Review of Information) is a specialized SaaS platform designed by the Joanna Briggs Institute to facilitate the entire lifecycle of systematic reviews. Architecturally, it is built to support the 10 distinct types of reviews recognized by JBI, including qualitative, quantitative, and scoping reviews. The platform's 2026 market position is solidified by its integration of standardized critical appraisal tools and a proprietary meta-analysis engine that automates statistical synthesis for researchers. Unlike general-purpose data analysis tools, SUMARI is technically optimized for high-fidelity evidence synthesis, ensuring compliance with global reporting standards like PRISMA. It provides a collaborative environment where multi-disciplinary teams can conduct blinded screening, rigorous critical appraisal using validated JBI instruments, and complex data extraction. By 2026, it remains the gold standard for healthcare institutions, academic libraries, and policy-making bodies that require verifiable, audit-ready research outputs. Its technical value proposition lies in the reduction of manual error during meta-aggregation and the streamlining of the path from protocol development to final manuscript generation.
Includes 13 validated JBI critical appraisal checklists integrated directly into the workflow for bias assessment.
Accelerate academic research through intelligent citation graph analysis.
Your personalized AI research assistant designed to synthesize complex information with source-grounded accuracy.
The high-velocity AI research engine for scientific literature synthesis and automated evidence mapping.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
A built-in statistical engine capable of performing fixed-effect and random-effects meta-analysis.
Supports the assembly of findings from qualitative studies into categorized themes.
Allows two or more reviewers to independently screen studies with conflict resolution workflows.
User-defined field generation for structured data harvesting from primary studies.
Hard-links the study protocol to the active project to prevent post-hoc bias.
Automates the creation of GRADEpro-compatible tables for evidence certainty assessment.
Researchers need to synthesize the efficacy of a new drug across 20 randomized controlled trials.
Registry Updated:2/7/2026
Run Meta-analysis
Synthesizing patient experiences of chronic pain management from qualitative interviews.
Hospital committees need to create evidence-based protocols based on a scoping review.