Mandolin is an AI company focused on obliterating the specialty drug paperwork that slows patient access to life-saving infused and injected medications. Founded in 2024 by repeat entrepreneurs Will Yin (CEO) and Rohit Rustagi (COO), the company targets the buy-and-bill model used for specialty drugs, where infusion centers and specialty pharmacies must purchase expensive medications, navigate benefits investigations and prior authorizations, administer treatment, and then secure reimbursement, a relay that today runs on manual processes and clipboards.
Mandolin deploys AI agents that automate tasks across this entire workflow, from patient referral through infusion and reimbursement. The agents handle benefits verification, prior authorization, and the reimbursement documentation that determines whether providers get paid accurately for high-cost therapies. By replacing manual coordination with software, Mandolin aims to reduce delays in patient access, cut administrative cost, and lower the financial risk that infusion providers carry when stocking expensive drugs.
The company has gained traction with serious customers, working with many of the nation's largest infusion providers, pharmacies, and health systems, including Vivo Infusion, FlexCare Infusion, OI Infusion, TwelveStone Health Partners, and Amber Specialty Pharmacy. This kind of reference base in a niche, high-stakes segment of healthcare operations signals that Mandolin's automation addresses a concrete and costly problem.
Mandolin raised a $40 million Series A in June 2025, backed by Greylock Partners, SignalFire, Maverick, and SV Angel, with notable angels including Jerry Yang (co-founder of Yahoo) and Guillermo Rauch (CEO of Vercel). Its earlier seed round was co-led by SignalFire and Maverick. The capital funds deployment of AI labor across several thousand infusion centers, specialty pharmacies, and health systems.
For infusion and specialty pharmacy operators, Mandolin offers a way to compress the buy-and-bill cycle and reduce reimbursement risk, with success ultimately depending on payer cooperation and the accuracy of agent-driven submissions in a tightly regulated reimbursement environment.