Buried in Papers, Starving for Answers

Scientific knowledge is expanding faster than any researcher can read. A single literature review can mean sifting through hundreds of papers, cross-referencing citations, and manually verifying claims — a process that eats up hours or days before a researcher even starts forming a hypothesis. Search engines return links, not answers, leaving the hardest part of research — synthesis — entirely up to the human.

What They're Building

AnswerThis is an AI research assistant built to answer scientific questions directly, backed by citations pulled from real published literature. Instead of returning a list of papers to sift through, AnswerThis reads across the scientific corpus, synthesizes an answer, and shows exactly which studies support each claim — letting researchers verify sources instead of hunting for them. The tool is designed to compress what used to be hours of manual literature review into a focused, citation-backed conversation.

By grounding every answer in traceable sources, AnswerThis aims to give researchers, students, and scientists a faster path from question to evidence-based answer, without sacrificing the rigor that scientific work demands.

Growth

AnswerThis raised a $500K seed round and was accepted into Y Combinator's Fall 2025 batch, giving the team access to YC's network of research-focused founders and early enterprise and academic customers as it builds out its citation engine.