About Journal Suggester

Connecting researchers with the perfect journals for their work through advanced AI and comprehensive data analysis.

32,000+

Academic Journals

120+

Countries

310

Subject Categories

11,000+

Open Access Journals

Our Mission

Our mission is to accelerate the dissemination of scientific knowledge by connecting researchers with the most appropriate publication venues for their work. We believe that finding the right journal shouldn't be a barrier to sharing important research with the world.

Through advanced AI technology and comprehensive database analysis, we make journal selection more efficient, accurate, and accessible to researchers worldwide.

Why Choose Us?

Save hours of manual journal research
Increase publication success rates
Discover new relevant journals
Access comprehensive journal metrics
Get AI-powered recommendations
Compare journals side by side

Key Features

AI-Powered Analysis

Advanced machine learning algorithms analyze your manuscript and match it with the most suitable journals.

Global Database

Access to 32,000+ academic journals from publishers worldwide, covering all research disciplines.

Smart Recommendations

Journals are matched on what they actually publish, then an AI model explains why each one fits your manuscript.

Quality Metrics

Comprehensive journal metrics including H-index, SJR, quartile rankings, and citation data.

How It Works

1

Submit Your Manuscript

Input your manuscript title and abstract, or upload reference files for analysis.

2

AI Analysis

Our AI analyzes your research and matches it with relevant journals from our database.

3

Get Recommendations

Receive personalized journal suggestions with detailed metrics and insights.

We're in Startup Phase

Journal Suggester is currently in its startup phase. We're building something revolutionary for the academic community and looking for passionate individuals to join our journey.

Seeking Investment

We're actively looking for investors who believe in transforming academic publishing

Building Our Team

Join us as we build the future of journal discovery and recommendation

Get Involved

Journal Suggester is an independent project. If you have feedback, found a wrong recommendation, or would like to collaborate on the data, statistics or design, we would love to hear from you.