AI-Powered Academic Literature Review
Tessera
Tessera is an AI-powered academic literature review platform that searches five major databases — Semantic Scholar, arXiv, OpenAlex, CrossRef, and PubMed — to find relevant research papers.
It generates structured paper summaries and cross-paper literature syntheses, visualizes citation networks with relationship classification, and extracts findings, methods, gaps, and conclusions into a searchable knowledge base.
Results can be exported as BibTeX, JSON, or a deployable static website. The interactive citation graph lets you explore how papers relate to each other, identifying clusters, influential works, and research gaps.
Architecture
Federated Search
Search across Semantic Scholar, arXiv, OpenAlex, CrossRef, and PubMed simultaneously. Results are deduplicated and ranked by relevance.
AI Summaries & Synthesis
Each paper gets a structured AI-generated summary. Collections of papers get cross-paper synthesis identifying themes, agreements, contradictions, and research gaps.
Citation Graph
Interactive visualization of how papers cite each other. Relationship types are classified (supports, contradicts, extends, etc.) for richer understanding of the research landscape.
Knowledge Extraction
Automatically extracts findings, methods, gaps, and conclusions from papers into a searchable knowledge base. Export as BibTeX, JSON, or a deployable static website.
Gallery
Tessera — Dashboard
Tessera — Paper Detail
Tessera — Citation Graph
Tessera — Literature Synthesis
Tessera — Knowledge Base
Tessera — Collection Detail