Sigmatic Sciences Powers AI Scientists with NVIDIA’s Latest BioNeMo Agentic Capabilities

The First Agentic Operating System for Life Sciences R&D

PRESS RELEASE

Already running NVIDIA BioNeMo in production, the SigmaticOS now leverages NVIDIA’s latest agentic innovations to connect AI agents, scientific software, and laboratory systems into traceable lab-in-the-loop discovery workflows.

Fort Lauderdale, Florida, USA, June 23, 2026 – Sigmatic Sciences, the first agentic operating system for life sciences R&D, today announced integration of NVIDIA BioNeMo Agent Toolkit within SigmaticOS, strengthening its ability to deploy AI Scientists that can reason, plan, and execute across the full scientific discovery lifecycle.

Powerful AI agents alone do not create scientific breakthroughs. They need scientific context, trusted data, specialized tools, and laboratory connectivity to operate effectively. SigmaticOS provides a scientific operating system that transforms hundreds of AI agents into an AI Scientist capable of orchestrating data, models, software, and experiments into a single traceable workflow. This enables research teams to move beyond isolated AI assistance and toward scalable, reproducible scientific discovery, with scientists always in the driver’s seat.

SigmaticOS has leveraged NVIDIA BioNeMo and Nemotron models in production since its inception. With the release of BioNeMo Agent Toolkit, SigmaticOS further expands its ability to orchestrate biological AI models, scientific software, enterprise data, and laboratory systems within a single coordinated research environment. Enabling governance, traceability, and scientific guardrails resulting in an agentic AI that can move beyond isolated experimentation and into real-world scientific operations.

NVIDIA BioNeMo Agent Toolkit provides the biological AI foundation for this transformation, delivering specialized models, agent frameworks, and infrastructure designed for life sciences. SigmaticOS provides the operating system that puts those capabilities to work, connecting AI agents to the tools, data, and laboratory environments required to conduct rigorous scientific research.

“Powerful AI agents are only part of the equation,” said Kevin Cramer, Founder and CEO of Sigmatic Sciences. “The AI Scientist we have built ensures every AI agent has the scientific context, access to trusted data, the ability to use specialized scientific tools, and a direct connection to laboratory execution. The world in which they operate is exactly what SigmaticOS provides.”

Through SigmaticOS, the capabilities of NVIDIA BioNeMo Agent Toolkit are orchestrated alongside more than 300 specialized scientific agents and connected across the entire discovery stack. This includes proprietary experimental data, any ELN/LIMS and laboratory automation infrastructure like Sapio Sciences, scientific literature and data resources from Elsevier, structural chemistry capabilities from the Cambridge Crystallographic Data Centre (CCDC), and advanced simulation platforms from Simulations Plus.

The platform also incorporates domain-specific biological AI models from the NVIDIA BioNeMo ecosystem, including OpenFold3 and Boltz-2 for biomolecular structure prediction, RNApro for RNA structure analysis, and ReaSyn for synthesizability assessment.

The result is a true lab-in-the-loop discovery system where an AI Scientist can continuously learn from experimental outcomes, refine hypotheses, and coordinate subsequent investigations. By connecting biological AI directly to scientific software and laboratory infrastructure, SigmaticOS helps researchers shorten the path from idea to experiment to insight.

Kevin Cramer added: “We’ve been running NVIDIA BioNeMo in production from the beginning, and the latest agentic capabilities strengthen our vision for AI Scientists that work alongside human researchers. SigmaticOS provides the scientific operating system. Together, we’re creating a new model for discovery where AI can reason across data, use specialized scientific tools, and interact directly with the laboratory as part of a single traceable workflow.”

Sigmatic Sciences will showcase its BioNeMo-powered AI Scientist workflows at the BIO International Convention, June 22–25 in San Diego.

-END-

For more information please contact:

Sigmatic Sciences
Kevin Cramer, Founder and CEO
Mike Hampton, Chief Commercial Officer
Dave Cooney, Head of GTM
info@sigmaticsciences.com

ICR Healthcare
Jessica Hodgson / Ashley Tapp
SigmaticSciences@icrhealthcare.com

To book a demonstration of SigmaticOS please contact:
dave.cooney@sigmaticsciences.com

About Sigmatic Sciences

Sigmatic Sciences, formerly HelixAI and a proud Sapio Sciences Company, is dedicated to transforming R&D by unifying tools and autonomous processes in a single platform, enabling scientists to deliver better medicines, faster.

We have created the Sigmatic Operating System (SigmaticOS), the only complete labin-the-loop platform for all scientists, allowing research to move from copilot to autopilot. SigmaticOS orchestrates 100+ agents across in silico workflows, lab automation, and model training with full traceability. By integrating scientific data from public, private and client sources with unlimited autonomous computation, SigmaticOS takes the pain out of drug discovery, closing the loop between computation and the bench, and putting human scientists into the driving seat.

Sigmatic Sciences is led by a team with decades of experience in science, AI and bioinformatics and backed by one of Europe’s leading healthcare investors, GHO Capital.

Find out more online at: https://www.sigmaticsciences.com/

About Lab-in-the-loop

Lab-in-the-loop is an iterative research framework that accelerates drug discovery by creating an iterative feedback cycle between computational models and physical experiments. In silico tools generate scientific hypotheses, which are tested in automated labs, with results being analyzed and used in refining the AI tools for the next cycle.

Legal Disclaimer:

EIN Presswire provides this news content "as is" without warranty of any kind. We do not accept any responsibility or liability for the accuracy, content, images, videos, licenses, completeness, legality, or reliability of the information contained in this article. If you have any complaints or copyright issues related to this article, kindly contact the author above.