Marissa Famularo

Verastar is a morning literature harness built by and for a busy vascular surgeon who can't read the hundreds of papers published in her field each month, yet can't afford to miss them. The insight: frontier models are superb at reading papers, but can't be trusted on numbers. Verastar wraps Claude Opus in a deterministic verifier: every statistic is located in the source text and gated before it renders, showing what it proved, not what a model asserted. A number that can't be found is never shown; verified numbers appear inline. Papers link to their PDFs and full text, saved work forms a searchable library, and connections tie active projects to new literature. Everything saved becomes a plain markdown file in a folder the clinician owns. Because that memory is an open folder, any agent she trusts can read it -- the seed of a research companion whole teams could build on. Verastar exists to bring doctors who haven't used AI into the fold, and give busy clinicians who never had time for research the chance to change their field. Built end-to-end with Claude Code, including 181 adversarial false-verify tests, by a physician who never coded before late 2025.