We envision a world where

accessing benefits
quality care
clear health information

is a right, not a privilege

Healthcare has become so complex to navigate, people on all sides of the care relationship feel burned out and alone. Patients are frustrated, lost and feel taken advantage of – providers are overwhelmed, overworked and feel unappreciated.
At Zeteo Health we are dedicated to improving this experience on all sides. We’re utilizing leading-edge AI chat technology, image capture and analysis, and our vetted research knowledge base to create
the virtual health advocate every patient deserves and the virtual health assistant every provider needs.
OUR MISSION
Provide personalized support for every health journey, so patients and providers can focus on what matters most.
Our Approach to Using AI
At Zeteo, we know that AI is an incredibly powerful tool with the capability to fundamentally change the healthcare experience for patients and providers. At the same time, as technologists, clinicians, and patients, we also recognize the risks of using generative AI without proper controls.

That's why our engineering and data science team–led by long-time AI thought leader Eric Landry (Babylon, Expedia, UT-Austin) and supported by Columbia, Johns Hopkins, and Yale-trained researchers–has built a number of safeguards and guardrails into our AI model.

While no system is perfect, and Zeteo AdvocateTM responses should not be treated as medical advice, we believe that the combination of these guardrails elevate the standard for responsible use of AI in a healthcare setting.

  • Trusted sources

    Each source that powers our model’s knowledge base has been individually vetted by a clinician or public health professional. Think of our knowledge base as an ever-growing library filled with only trusted and vetted books.

  • Professional quality control checks

    We have clinicians and public health professionals on staff because we believe in actively evaluating accuracy of test responses generated from our knowledge base.

  • Accuracy metrics

    Like faithfulness (factual consistency) and answer relevancy are tracked and used to monitor and improve quality.

  • Real time monitoring and optimization

    Enables the system to reduce hallucinations (incorrect answers generated by AI) and increase dependability.