Agentic AI is changing how research is done. AI scientists can read papers, propose hypotheses, call models, and determine which experiments to prioritize next. First proving their value in software engineering, coding agents now write, test, and ship production code. Scientific research can be more demanding and iterative. Researchers continually evaluate evidence, refine hypotheses, and run experiments that shape subsequent decisions. Even failed experiments can lead to unexpected insights.

Scientific problems also often require domain-specific tools, for example, to fold a protein or characterize a molecule. Orchestrating and operating these tools can be challenging. Similar packages may have vastly different environment requirements or APIs. A general-purpose agent might recognize that a task calls for protein folding or molecular docking, but not which model to run, how to format the request, or which parameters matter.

NVIDIA BioNeMo Agent Toolkit closes that gap.…