AI-Powered Systematic Review & Meta-Analysis
Master the Evidence, Automatically
If you're conducting a systematic literature review or meta-analysis, Gatsbi Reviewer empowers you to skip the manual burden and focus on insight. From intelligent study selection to automated data extraction , bias assessment and statistical synthesis — all in one platform. Just input your research topic, select relevant studies, and let Gatsbi generate structured, publish-ready evidence synthesis in minutes.
Whether you're writing a research paper, policy brief, or grant proposal, Gatsbi Reviewer ensures methodological rigor, transparency, and speed.
Powerful Features for Effortless Review Writing

Smart Study Screening
Automatically retrieve, rank, and screen relevant studies based on your topic — no manual searching required.

Data Extraction Automation
Extract effect sizes, confidence intervals, sample sizes, and more from eligible papers using AI-powered parsing.

Built-in Meta-Analysis Engine
Run fixed-effect or random-effects models, generate forest plots, funnel plots, heterogeneity metrics (I², Q), and publication bias assessments — all with zero coding.

Structured Manuscript Generation
Automatically generate an SLR or meta-analysis draft in structured format, including Abstract, Methods, Results, and Figures.

Bias & Quality Assessment
Apply RoB (Risk of Bias) or GRADE-like quality scoring to included studies, guided by AI suggestions.

Citation-Aware Writing
Preserve and format all citations accurately using direct access to Google Scholar data.
Why Choose Gatsbi Reviewer

Comprehensive Evidence Coverage
Covers everything from search to synthesis — including data, visualizations, and manuscript generation.

Time-Saving Automation
Complete in 15 minutes what would normally take weeks.

Methodologically Sound
Built-in PRISMA flow, standardized metrics, and reproducible outputs ensure compliance with academic standards.

Easy to Use
No statistics or programming skills needed — ideal for students, researchers, and professionals.
