Edison Analysis
Edison Analysis is a next-generation scientific data-analysis agent built by Edison Scientific. It is the analytical engine underpinning their AI Scientist platform, Kosmos, and it’s available both on Edison’s platform and via API. Edison Analysis performs complex scientific data analysis by iteratively building and updating Jupyter notebooks in a dedicated environment; given a dataset plus a prompt, the agent explores, analyzes, and interprets the data to provide comprehensive insights, reports, and visualizations, very much like a human scientist. It supports execution of Python, R, and Bash code, and includes a full suite of common scientific-analysis packages in a Docker environment. Because all work is done within a notebook, the reasoning is fully transparent and auditable; users can inspect exactly how data was manipulated, which parameters were chosen, how conclusions were drawn, and can download the notebook and associated assets at any time.
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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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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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GPT-Rosalind
GPT-Rosalind is a purpose-built frontier reasoning model developed by OpenAI to accelerate scientific research across biology, drug discovery, and translational medicine. It is designed specifically for life sciences workflows, where researchers must navigate large volumes of literature, experimental data, and specialized databases to generate and validate new ideas. It combines deep domain understanding in areas such as chemistry, genomics, protein engineering, and disease biology with advanced tool-use capabilities, allowing it to interact with scientific databases, analyze experimental outputs, and support complex, multi-step reasoning tasks. It can assist with evidence synthesis, hypothesis generation, literature review, sequence interpretation, and experimental planning, helping scientists move faster from raw data to actionable insights. GPT-Rosalind transforms complex, time-intensive research processes into more efficient AI-assisted workflows.
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