The open-source AI workbench for scientific research

Give it a goal. It reads the literature, writes and runs code, runs the experiments, and writes up what it found.

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OpenScience is an AI workbench for scientific research. You give it a goal, and it works through the research loop the way a capable collaborator would. It reads the papers that matter, forms a hypothesis, writes and runs code, runs experiments on real compute, queries the major scientific databases, and writes up the result. It runs as a workspace in your browser and works with any frontier or open-weight model from Anthropic, OpenAI, Google, and dozens of other providers, using your own API keys. No account is required.

It is model-agnostic, open source, and built to do real work in machine learning, biology, physics, and chemistry.

What it does

• Runs the whole loop. Literature review, hypothesis, code, experiment, analysis, and write-up, in one continuous session.
• Research agents. A research agent by default, plus biology, physics, and ml specialists, with critique and literature-review sub-agents and a read-only plan mode.
• 290+ skills. Training (DeepSpeed, PEFT, TRL), evaluation, dataset work, molecular and clinical biology, cheminformatics, papers and LaTeX, figures, and cloud compute (Modal, Tinker, and others).
• Scientific databases as tools. UniProt, PDB, Ensembl, ChEMBL, PubChem, arXiv, OpenAlex, Semantic Scholar, and around 30 more, queryable directly by the agent.
• A real workspace. A browser UI with a file tree, an editor, a terminal, session history, and inline rendering for molecules, structures, genomes, and plots.
• Extensible. LSP integration, MCP servers, plugins, custom agents and commands, and a TypeScript SDK.

Install