Ellen Schrader

Atlas: every lab has a taste. AI threatens to homogenise scientific research: every lab asks the same models to run its literature search, summarise papers, and come up with ideas - and every lab gets the same consensus answer. Atlas is the bet against that. It doesn't make Claude smarter; it gives Claude your lab's perspective. Atlas builds a shared, searchable memory from a lab's literature: deduplicated papers, semantic search, topic maps, and grounded digests of what's new. As researchers read, discuss, and curate papers, Atlas learns the lab's evolving scientific taste. Through MCP, Claude can securely read that memory (owner-controlled and fully audited) and answer a question a generic literature search can't: is this idea novel for our lab? It drafts related-work sections in which every citation is verifiable, and even generates figures in the visual style the lab has implicitly developed over years. Instead of every lab converging on the same AI, Atlas gives every lab an AI shaped by its own scientific taste. https://atlas-papers.vercel.app/papers