Sushant Shankar

Co-Founder & CEO Clint Health

Last Reviewed: September 19, 2026

Executive Summary

Sushant Shankar is the co-founder and chief executive of Clint Health, which sells a clinical intelligence platform designed to act at the moment a clinical decision is made rather than afterwards. The problem it addresses is a gap between what medicine knows and what gets done: guidelines change, new therapies arrive, and a specific patient sitting in a specific clinic frequently does not get matched to the treatment or the trial for which they qualify, because nobody has the time or the data assembled to notice. Clint automates that matching at the point of care, which gives it two distinct customer bases - pharmaceutical and biotech companies concerned with drug adoption and trial recruitment, including Amgen, Janssen, Vertex, Merck and AstraZeneca, and health systems concerned with guideline adherence and closing care gaps. Shankar co-founded the company with Rajesh Dash, a Stanford cardiologist who encountered the problem clinically and now chairs the business. Shankar’s own background is the computational half: a BS from Berkeley, an MS from Stanford, and executive roles applying machine learning at consumer internet scale in ad-tech and e-commerce before turning that experience on medicine.

Career Highlights

• Co-founded Clint Health with Rajesh Dash, MD, PhD, a Stanford associate professor of cardiovascular medicine and the company’s chairman, and leads it as CEO.
• Built what the company describes as the first automated clinical intelligence platform, the product of roughly eight years of development, making medical data actionable at the point of care.
• Won life-sciences customers including Amgen, Janssen, Vertex, Merck, AstraZeneca, Alnylam, Apellis, Illumina and Esperion.
• Established clinical and professional-society relationships including Stanford and the American College of Cardiology.
• Built data partnerships with Datavant, Practice Fusion, Veradigm and HealthVerity, the infrastructure layer a therapy-matching product depends on.
• Applied machine learning to more than a billion users across ad-tech and e-commerce in earlier Silicon Valley executive roles, including at Reflektion and 33Across.
• Worked as a consultant at Bain & Company and in research at Stanford before moving into operating roles.
• Recruited a senior team from SAP, Oracle, Alteryx and WorkSpan across marketing, revenue, clinical operations and information security.

Professional Journey

Shankar’s training sits at the intersection the company now occupies. He took a BS at UC Berkeley and an MS at Stanford, with work in computational biology, and then spent the first part of his operating career not in healthcare but in consumer internet software. He held executive positions at Silicon Valley companies applying machine learning at very large scale - personalisation in e-commerce at Reflektion and advertising technology at 33Across, work the company summarises as machine learning applied to more than a billion users. He also spent time consulting at Bain & Company and in research at Stanford.

That combination turns out to be unusually well-matched to the problem Clint addresses. Recommending a therapy to a clinician is, structurally, a matching and ranking problem over a large, messy, incomplete dataset under real-time constraints, which is what recommendation systems in e-commerce and advertising do. The differences are that the data is regulated, the consequences are clinical, and the user is a physician with two minutes rather than a consumer browsing.

The clinical half of the founding team supplies what the technical half cannot. Rajesh Dash spent twelve years on the Stanford faculty as an associate professor of cardiovascular medicine and identified systemic care gaps through his work with the Stanford South Asian Translational Heart Initiative, a programme addressing a population with markedly elevated cardiovascular risk that standard guidelines served poorly. Encountering that problem from inside a clinic rather than from a dataset is the origin of the company, and Dash serves as chairman while Shankar runs it.

Clint invested roughly eight years building the platform before it reached its current form, which is a long development arc and reflects the difficulty of the underlying work - ingesting clinical data from disparate systems, reconciling it, and producing a recommendation a physician will act on. That required a data layer as much as an algorithm, and the company has built partnerships with Datavant, Practice Fusion, Veradigm and HealthVerity to assemble it.

Commercially the product is sold into two directions from a single capability. Pharmaceutical and biotech companies buy it to reach the patients who qualify for a therapy or a trial, which addresses their two hardest problems, adoption and recruitment; the customer list runs to Amgen, Janssen, Vertex, Merck, AstraZeneca, Alnylam, Apellis, Illumina and Esperion. Health systems and professional bodies, including Stanford and the American College of Cardiology, buy it for guideline adherence and care-gap identification. Shankar has built the senior team around that dual market, bringing in executives from SAP and Oracle in marketing, Alteryx and WorkSpan in revenue, and clinical trial operations and security specialists, with the company based in Redwood City, California.

Education

Stanford University

MS, Computer Science (bio-computation)

University of California, Berkeley

BS, Electrical Engineering, Computer Science and Mathematics

The institutions and degree levels are confirmed on Clint Health’s own team page. The specific fields come from commercial aggregators, and no graduation years were found.