Citare

One person processes a paper with AI; everyone should inherit the result. LLMs can read papers, but PDF reading is not claim infrastructure. PDFs are long, messy, and parsed inconsistently: one run may drop a mediator or boundary condition, while another turns “associated with” into “causes.” And the more important the paper, the more often this unstable process is repeated. For field-defining papers, it is plausible that a million people will ask AI to read the same paper over the next decade. That wastes energy and amplifies citation drift. Citare uses Claude Opus 4.7 to convert papers into reusable claim graphs. Each claim stores source text, page numbers, evidence type, causal strength, safe citation verbs, boundary conditions, and integrity warnings. Other tools return metadata; Citare returns the actual claim and makes it reusable through an open database and CitareMCP. Try it now at https://citare.dev/