Synthical

Synthical is an AI-powered research environment designed to organize, discover, and analyze scholarly articles across multiple domains. It provides personalized feeds, advanced filtering, and collaborative features to help researchers stay current with new trends and build structured libraries of literature. The interface emphasizes easy access to recent publications, prominent institutions, and conference highlights, enabling efficient research workflows.

How it works

• Centralized space to browse, search, and organize articles.
• Personalizable feeds curate new papers and trends based on interests and history.
• Folders, favorites, and profiles help you manage and share your literature collection.
• Comprehensive filtering supports 10+ categories and disciplines to narrow down results.
• Quick access to popular organizations, conferences, and authors to discover leading work.

Core Features

• AI-powered search for fast, relevant results across a large corpus of articles
• Personal feeds that surface new trends and relevant papers
• Folders, favorites, and profile pages for organizing and collaborating on research
• Multi-criteria filters (discipline, venue, author, institution, year, etc.)
• Article previews, summaries, and quick context to accelerate understanding
• Access to conference highlights and popular organizations for staying updated
• Sign-in and personalized settings to tailor recommendations
• Integration-ready for exporting references or sharing collections
• Recommendations and discovery tools to help identify related work

Used For

• Researchers who need to manage large literature reviews
• Students building literature bases for theses and dissertations
• Teams tracking developments across multiple scientific domains
• Anyone seeking a streamlined way to stay current with scholarly publications