Harnessing Agentic AI with Viz.ai
Dr. Chris Mansi, a former UK neurosurgeon and Stanford GSB alumnus, cofounded Viz.ai to solve what he saw as an information problem in stroke care. Large vessel occlusion (LVO) strokes respond dramatically to mechanical thrombectomy, yet fewer than 10 percent of U.S. LVO patients received the procedure, largely because diagnosis and specialist notification took hours. Viz.ai’s AI-powered software cut that process to minutes, received the first FDA de novo clearance for AI triage software in 2018, and aligned the economics for hospitals, payers, and patients, aided by Medicare’s new technology add-on payments.
The case traces Viz.ai’s path from seed funding by Eric Schmidt to $250 million raised and adoption by roughly 2,000 hospitals, and its push into generative and agentic AI through Viz Assist, a care coordination platform that summarizes health records, flags gaps against clinical guidelines, and drafts clinical documentation. By 2026, Viz.ai offered 67 disease pathway modules and aimed to cover thousands of disease states. Yet it no longer stood alone: Microsoft, Epic, GE Healthcare, and Siemens were all bringing AI to clinical care with far greater scale and larger installed bases.
Mansi must decide how to keep Viz.ai indispensable. Should it go deep on disease-specific modules or pursue a broad platform play? Can it shift from selling individual clinical applications to an enterprise software sale, attract AI talent at scale, and compete with much larger players, or should it partner with, or be acquired by, a major technology firm?
Learning Objective
Students will learn to:
- evaluate AI deployments in healthcare by weighing clinical benefit against buyer economics;
- analyze how aligned incentives and reimbursement, such as NTAPs, drive adoption of new medical technology;
- assess go-to-market strategy across clinical and administrative buyers; and
- weigh platform versus point-solution strategy, and partnering versus competing, as large AI players enter the market.