scienceOS
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.
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Sciscoper
Sciscoper is an AI powered research assistant that is used to streamline and accelerate the literature review process for STEM researchers, academics, and R&D teams. Researchers often deal with hundreds or thousands of scientific papers scattered across different sources, making it difficult to extract meaningful insights efficiently.
Sciscoper solves this by using AI and natural language processing to automatically:
Summarize scientific papers and research findings.
Extract key insights, concepts, and relationships across documents.
Generate literature reviews with citations in multiple reference styles.
Organize and index papers into a structured, searchable knowledge base for easy discovery.
This allows users to focus less on manual reading and note-taking, and more on analyzing results, identifying research gaps, and producing new scientific knowledge.
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Edison Scientific
Edison Scientific is an AI platform designed to automate and accelerate scientific research, enabling users to move from hypothesis to validated results within a single environment. The platform integrates literature synthesis, data analysis, and molecular design workflows, allowing research teams to complete end-to-end scientific investigations at dramatically increased speed. At its core is Kosmos, an autonomous research system that performs hundreds of research tasks in parallel, transforming multimodal datasets into comprehensive reports with validated findings and publication-ready figures. Kosmos synthesizes scientific literature, public databases, and proprietary datasets, identifies novel therapeutic targets, uncovers biological mechanisms, and supports the iterative design and optimization of molecular candidates. Validated in real research settings, Kosmos has demonstrated the ability to achieve results that typically require months of human effort in a single day.
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FutureHouse
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.
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