Sciscoper

scienceOS is an AI-powered research platform built to accelerate scientific literature workflows by giving researchers fast, reliable access to a massive database, more than 225 million research papers via a chat-based interface. The core “AI science chat” lets you ask questions, get answers grounded in published literature, and even generate tables or diagrams summarizing findings. If you upload PDFs, the “multi-PDF chat” can parse up to eight documents per session and extract key passages, figures, and tables to help you digest papers quickly; it can also generate structured summaries of papers (e.g., intro, methods, conclusions), highlighting main findings, limitations, and key data. Alongside that, scienceOS includes an AI reference manager; you can store and organize up to 4,000 PDFs or citations in a personal or shared library, import external references (e.g., from Zotero), and chat with your own collection, useful for drafting literature reviews and building bibliographies.

FutureHouse is a nonprofit AI research lab focused on automating scientific discovery in biology and other complex sciences. FutureHouse features superintelligent AI agents designed to assist scientists in accelerating research processes. It is optimized for retrieving and summarizing information from scientific literature, achieving state-of-the-art performance on benchmarks like RAG-QA Arena's science benchmark. It employs an agentic approach, allowing for iterative query expansion, LLM re-ranking, contextual summarization, and document citation traversal to enhance retrieval accuracy. FutureHouse also offers a framework for training language agents on challenging scientific tasks, enabling agents to perform tasks such as protein engineering, literature summarization, and molecular cloning. Their LAB-Bench benchmark evaluates language models on biology research tasks, including information extraction, database retrieval, etc.