Frontier AI labs have warned that their technology could help develop dangerous bioweapons.
Now, a startup says it has developed a defense. On Wednesday, Radical Numerics announced that it has developed a new edge model called Omnii Defense that is designed to flag natural and AI-engineered pathogens using a laptop and a USB gene sequencer. It can also run without an internet connection, allowing researchers in the field with spotty connections to use it. Though many scientists say AI-made bioweapons are a low-likelihood threat, Radical Numerics hopes its technology will help researchers and public health officials identify emerging biological threats.
Eric Nguyen, cofounder and CEO of Radical Numerics, says he sees a coming arms race in biodefense similar to what’s playing out in cybersecurity, where threat actors and security defenders are leveraging AI in an attempt to gain an edge.
“We felt that the biosecurity space was far behind on the defense side,” he says.
Nguyen and his cofounders were part of the research team behind Evo and Evo-2, open-source DNA foundation models they worked on during their doctoral research at Stanford University. They founded Radical Numerics in 2025.
The San Francisco–based company recently made waves after rolling out Omnii, a new genome language model built on different types of biological information beyond DNA, including RNA, proteins, and epigenetic signals. In October, Radical announced that it used Omnii to create custom bacteriophages, viruses that infect and kill specific bacteria, targeting a drug-resistant strain of E. coli. Its cocktail was used to treat a sick patient, with special permission from the Food and Drug Administration.
Another AI biotech startup, Tabula Bioscience, was also involved in that research, but Radical didn’t disclose the partnership in its announcement last month. The omission led Harvard geneticist George Church, who was an adviser to both companies, to resign from his role at Radical last week.
Omnii Defense, the company’s latest tool, makes multiple predictions about a sequence, including the odds of it being pathogenic or AI-generated and what taxonomic group it most closely resembles. The model assigns a genome a “threat score” between zero and one that combines the likelihood of unnaturalness with functional predictions. The higher the score, the higher the threat.
Earlier biodefense tools, such as the federally funded Finding Engineering-Linked Indicators, or Felix, can compare genetic sequences of interest against libraries of known organisms, essentially searching for cataloged matches. That can be helpful in a scenario where a bad actor has made a few tweaks to an existing pathogen. But they aren’t designed to make predictions in the way that Omnii is.
