Synthetic Sciences Releases OpenScience: An Open-Source, Model-Agnostic AI Workbench for Machine Learning, Biology, Physics, and Chemistry Research

AI Workbench for Machine Learning, Biology, Physics, and Chemistry Research">

Synthetic Sciences has released OpenScience , an open-source AI workbench for scientific research. It is licensed under Apache 2.0 and runs on your own infrastructure. The research team frames it as an open alternative to Anthropic’s Claude Science , launched in late June 2026.

The pitch is direct. Scientific AI tooling should not be owned by one vendor. OpenScience keeps the workflow open, the models swappable, and the data local. It is an independent project, not affiliated with or endorsed by Anthropic.

OpenScience is a browser-based workspace backed by a local agent runtime. You give it a research goal. It then works through the loop a capable collaborator would follow.

It reads relevant papers, forms a hypothesis, writes and runs code, and runs experiments. It queries major scientific databases and writes up the result. All of this happens in one continuous session.

The tool is model-agnostic by design. It works with any frontier or open-weight model, using your own API keys. No account is required to start.

Installation uses npm. The command is openscience , and it opens the workspace in your browser.

The first run offers three options: Atlas managed models, your own provider keys, or free demo models. You can also skip a global install. Running npx synsci does the same thing in one step.

OpenScience runs a local server. That server hosts the workspace UI, the agent runtime, and the tool layer. The agent plans with a research harness and calls tools.

Those tools include the shell, editor, LSP, MCP servers, scientific connectors, and skills. The agent streams its work back to the browser as it runs.

Models are routed per request . You pick the model from the model selector in the workspace. So you can switch providers or run local models without changing anything else.

Your keys stay on your machine. Sessions, artifacts, and provenance are stored on disk. They can be shared as links.

Four things make the runtime useful for real work:

Extensibility is a first-class feature. OpenScience supports LSP integration, MCP servers, plugins, and custom agents. It also ships a TypeScript SDK.

There is an optional managed layer called Atlas . Atlas gives a curated set of frontier models billed from a prepaid wallet. It also adds a persistent research graph and cloud compute. OpenScience works with Atlas but never requires it.