Simulated conversations to scale healthcare training and evaluation.
Hi everyone, we’re Vrishank and Tigran, the team behind Soma Lab.
tl;dr: Soma Lab creates AI-simulated conversations to scale healthcare training. Students and providers practice with our AI patients to build skills and get evaluated.
The Problem: Healthcare Training and Evaluation Isn’t Scalable
Healthcare still relies on slow, expensive methods like role-playing, in-person evaluations, and one-on-one interviews. These outdated approaches not only create bottlenecks in education and hiring but also cost institutions hundreds of thousands of dollars annually in faculty time, actor fees, and administrative overhead. Scaling these processes is critical, but traditional methods make it nearly impossible.
While governments and accrediting bodies are pushing to expand healthcare workforces by increasing the number of schools and seats, the real bottleneck lies in non-didactic training. Schools have figured out how to scale lectures and coursework online, but they can’t scale the hands-on, interactive training required to meet competency-based accreditation standards like CACREP.
Adding to the challenge, it is illegal to practice counseling without direct clinical supervision in the classroom or the proper licenses. Students can’t even practice these conversations with friends or family legally, which leaves schools dependent on expensive, resource-intensive methods like faculty supervised role-playing.
Soma Lab uses AI to create realistic, interactive conversations with patients that allow students and professionals to practice and be evaluated anytime, anywhere. Our simulations replace costly methods with scalable alternatives, saving institutions significant time and money. Our system provides a legal, scalable solution for hands-on training, enabling schools to bypass these restrictions, meet accreditation requirements, and expand rapidly without sacrificing quality.
Therapy programs use Soma Lab to train students with AI patients, reducing reliance on actors. Companies use AI patients to assess job applicants and onboard new hires efficiently. Medical and social work programs prepare learners for real-world challenges without the need for resource-heavy manual evaluations.
In just 3 weeks, we were able to close 30 pilots with institutions like the University of Pennsylvania, Virginia Tech, University of Sydney, John Carroll University, and Western Carolina University.
We met at the University of Chicago after joining the same fraternity. Vrishank failed a clinical communications test and couldn’t afford the $9,000 tutor fee. So instead, we built an AI clinical communications coach. Vrishank's score shot up, so we said screw it and launched the tool. In 3 weeks, we hit $5k MRR and 2.5k users. Seeing the impact this would have if applied to all of healthcare, we decided to build the AI infrastructure for healthcare training and evaluation.
While in high school, Vrishank created a healthcare education app, which scaled to 120,000+ downloads in 6 months. Tigran was the lead machine learning researcher in a bioinformatics lab at the Luddy School of Informatics.
Share this with anyone in healthcare or education who trains, hires, or evaluates students and professionals.