Dante Suzuki spent the summer before his senior year of high school in a Georgetown University Medical Center lab, watching zebrafish twitch under a seizure-inducing drug and trying to teach a computer to spot the stages of epilepsy.
That summer set the trajectory for the University of Utah computer science student, who is now the co-founder of Autona, a software hub built to automate manual, time-consuming work in biomedical research labs.
Suzuki founded the company with fellow University of Utah computer science student Haley Young. Young came to the U as a first-generation college student, building her path as she went. Physics became a minor. Information systems, which bridges technical work and the wider world it operates in, became another.
Her time at the U has been driven by a pull toward unfamiliar territory, from peer advising to hackathons, research, and an Adobe Student Ambassador role. When Suzuki described what he was building, she saw a chance to put what she had been learning to work on a real problem.
“Instead of offering individual software to research labs, we offer a hub of generalized software to automate otherwise manual, time-consuming tasks,” Suzuki said.
Many research labs sit on stacks of images and video that resist automation unless someone builds a custom machine learning model, and most labs do not have the time or staffing to do that. Autona writes generalized software targeting those bottlenecks, with the aim of fast deployment and accurate results.
The first pipeline is in beta. It performs automated vessel morphometry from H&E histology — measuring the shape and structure of blood vessels in stained tissue samples — a task researchers traditionally do by hand, slide after slide. The team is also preparing an abstract for submission to the RANGE journal.
Suzuki, who grew up in Washington, D.C., traces his path into computer science back to a long-running interest in games. That interest led him to plan a career in the field and ultimately to enroll at the U.
The Georgetown lab job, where Suzuki worked as a program engineer tracking PTZ-induced epileptic movements in zebrafish, planted the practical seed.
“During this time, LLMs like ChatGPT and Claude were not as developed or popular as they are today,” Suzuki said. “As a result, developing machine learning models by hand was a slow, difficult process.”
That has changed.
“Now with the developments of Claude Code, developing complex models is becoming fast and exceedingly viable,” Suzuki said.
The company took shape this past spring through Lassonde DevLab, the software development arm of the Lassonde Entrepreneur Institute. Suzuki spent the semester there building Autona and working on projects for Storyline Health.
Young carried the company forward at Lassonde Demo Day, where she showcased Autona with a poster outlining the team’s progress.
“Being able to innovate alongside others who are doing the same allows each member of the cohort to learn about new technology, techniques, and business strategies from one another,” Suzuki said.
He said he has picked up a lot about working with LLMs, outreach and the networking that puts a young company in front of the right researchers.
That networking matters because the next year is built around it. By summer 2026, Autona aims to launch three projects in collaboration with researchers at the U, Georgetown University and the University of Maryland, putting the company’s software in three different labs at three different institutions within roughly a year of its founding.
Learn more about Autona at autonaintegratedsystems.lovable.app.
