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Pablo Bermudez-Canete

Pablo Bermudez-Canete

Co-Founder & CEO @ Paratus Health (YC W25), Stanford CS

Palo Alto, California, United States
ycombinator
Joined October 2025
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Summary

Pablo Bermudez-Canete is a driven young entrepreneur and AI student from Stanford University who co-founded Paratus Health. His company focuses on leveraging AI to automate patient management for outpatient clinics, aiming to streamline operations, reduce administrative burden, and enhance patient care through voice-enabled autonomous agents integrated with EHR systems. ycombinator+3
A participant in the Y Combinator Winter 2025 batch with Paratus Health, Pablo put his Stanford studies on hold to fully commit to his startup. This decision highlights his dedication to bringing his AI-driven healthcare solution to market and his understanding of the value of accelerator programs in the startup ecosystem. ycombinator+2
Pablo demonstrates a strong academic background in Computer Science, Artificial Intelligence, and Economics from Stanford University, complemented by research experiences in Biomedicine at Brown University and Economics at Boston College. This interdisciplinary foundation likely informs his approach to developing innovative healthcare technology. asbarcelona
He is a published researcher, co-authoring an article in npj Digital Medicine titled "Optimizing AI solutions for population health in primary care" in July 2025. This publication reflects his engagement with the broader implications of AI in healthcare, particularly concerning population health management, equitable outreach, and value-based care. google+1

Work

Education

Writing

Optimizing AI solutions for population health in primary care

July 1, 2025

Co-authored a paper discussing how AI can move beyond individual patient encounters to address population health management challenges in primary care. The paper emphasizes integrating longitudinal patient data, automating proactive outreach, and mitigating disparities to improve health equity and reduce administrative burden. It highlights the potential of AI to facilitate early intervention and benefit value-based care models.

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