open-science

Why we included this project

Researchers who want AI assistance without sending their lab data to a cloud service will find this workbench a straightforward fit: it runs on their own computer, and they can point it at whichever model they already use. You describe a task in plain language, and the lead agent, backed by specialist sub-agents and a reviewer, reads local files, runs Python and R code, searches the web, and calls scientific data connectors before handing back reports, tables, and figures. Every step lands in an activity history you can inspect, so the output stays reproducible and auditable. Out of the box, the bundled skills and connectors cover bioinformatics, genomics, and drug discovery most deeply, and the architecture leaves room to add other disciplines. That traceability is what makes it useful for teams that need to defend exactly how a result was produced.