Yaya Ali
Founder & CEO at DrunR
Seattle, Washington, United States
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Yaya Ali is the Founder and CEO of DrunR, an AI-powered behavioral intelligence platform helping people navigate metabolic health and GLP-1 treatment journeys. A first-generation college graduate and immigrant, Yaya has spent more than a decade building enterprise software, data platforms, and AI-enabled products.
His current work focuses on a challenge that affects millions of people: helping patients make better decisions between healthcare visits. Through DrunR, he is exploring how AI can move beyond information retrieval and become a trusted partner for real-world decision-making.
Yaya is passionate about entrepreneurship, product development, healthcare innovation, and the future of AI. He regularly speaks about building startups, designing trustworthy AI systems, and translating emerging technologies into practical solutions that improve people's lives.
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From Chatbots to Decision Systems: What Building an AI Health Startup Taught Me About Future of AI
Over the last year, building DrunR forced us to confront a question that many AI teams will face sooner than they realize:
What happens when AI moves beyond answering questions and starts helping people make real-world decisions?
In healthcare, the consequences of a recommendation can impact a person's health, treatment success, and quality of life. We quickly learned that large language models alone were not enough. We needed structured knowledge, grounded data, explainable scoring systems, feedback loops, and a way to connect AI recommendations to real-world outcomes.
In this session, I'll share lessons learned while building an AI-powered platform for metabolic health and GLP-1 care. We'll explore the difference between information systems and decision systems, common mistakes startups make when integrating AI into high-stakes environments, and why the next generation of AI products will need to move beyond chat interfaces.
Whether you're building a startup, AI product, or enterprise platform, you'll leave with practical insights on designing AI systems people can trust
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