Every Pegasi founder spent years inside oncology departments before writing a line of code. That context shapes every product decision we make.
Former attending oncologist at MD Anderson Cancer Center. Led a 7-year study on multi-modal early detection of colorectal cancer. Published 14 peer-reviewed papers on FHIR-based clinical data interoperability. Co-inventor of Pegasi's core diagnostic fusion patent.
Previously Principal Research Scientist at IBM Health. PhD in Biomedical Informatics from Johns Hopkins. Designed the Pegasi knowledge graph architecture and the continuous model retraining pipeline that processes 1,200 new cases per day.
Former VP of Health System Partnerships at Veracyte. Managed the operational launch of Pegasi's first three hospital deployments and built the clinical implementation methodology used across all 12 partner sites.
Every model update requires a retrospective validation against at least 1,000 de-identified cases before it touches production. We do not ship based on benchmark scores alone.
PHI never leaves your institution's environment. Pegasi's federated model means we improve on your data without seeing your data. SOC 2 Type II audited annually.
Our product team runs monthly working sessions with oncologists at partner sites. Alert fatigue, false-positive rates, and workflow friction are tracked as rigorously as model performance.
We are hiring oncology data scientists, clinical integration engineers, and a head of regulatory affairs. If you want your work to matter in a patient's chart, not just a benchmark leaderboard, talk to us.
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