HealthUnity Research & Development​

The next generation of digital health information: AI models trained on domain knowledge and health data for medical information that is accessible, credible, and easy to understand for all

Democratize Healthcare Knowledge

Imagine being able to go to one source for personalized,
trustworthy information on all health and well-being needs.


Medical queries translated into a simple, easy-to-understand language
through machines trained on domain expertise and data.

Preventative Care

Symptom-based Navigation

Dealing with a Chronic Disease


Think of the AI Health Navigator as a next-gen WebMD or a Wikipedia for Healthcare that is more interactive, more understandable, and more personalized – transforming the way we understand our own health.

Domain expert medical information delivered in a clear and simple language that demystifies individual health conditions and supports well-being.

Ask any question about any symptoms or health conditions and engage in an interactive conversation with the AI Health Navigator

Sync personal data from wearables, health tech devices, apps, and health history records for a more thorough look at how behaviors may impact an individual’s current health state

Trustworthy recommendations and in-depth clinical information from credible domain expert resources

All in an easy-to-understand language that is accessible and inclusive

Addressing Current Health Information Issues:

  • Siloed data in healthcare
  • Generative AI lacking domain knowledge
  • Credible web domain knowledge is available, though difficult to understand
  • No current holistic view of the patient

Bridging Data Silos in Healthcare

Developing a more advanced knowledge generator
Large scale connected data enabled through renowned interdisciplinary team expertise in collaboration with leading research institutes
A 360° holistic and longitudinal view of each person’s individual health

Combining Knowledge and Tools:

Designed with a user-friendly interface providing an easy, interactive experience with individualized support

  • Generative AI
  • Multimodal and Longitudinal Datasets
  • Domain Knowledge
  • Personal Information
  • Apps: Personicle and AI Health Navigator
  • AI Assisted Navigation

Harnessing the Power of AI

Large Language Models Based on Domain-Specific Knowledge and Multimodal Heterogeneous Health Datasets 

Today’s online resources for medical information offer credible healthcare expertise though the terminology is highly clinical and can often be difficult to understand.

Enter Generative AI – Powerful tools with enormous potential.

HealthUnity’s AI Health Navigator is the first digital health platform to combine domain-specific knowledge, open data knowledge, and privacy-protected personal health information using foundation models to navigate enormous amounts of data for instantaneous health information that would not otherwise be humanly possible. 


The Expansive Data Universe

Generative transformer language models trained on near-limitless digitally published domain content including in-depth medical and biomedical information from medical books, journals, publications, research papers, and medical websites

We are unlocking the potential of large-scale AI-driven data in healthcare via open knowledge and an open community.

Enabling inclusive, credible, and easy-to-understand medical information and resources for personal and societal health management.

We plan to extend beyond patients and practitioners, becoming the go-to platform for scientists, researchers, and industry as a large-scale data source of information for clinical trials and drug development.

AI Health Navigator Mission

Make healthcare knowledge accessible and understandable for everyone.

Empower every patient to better understand and navigate their own health.

Bridge key stakeholders in a patient’s health journey – from clinical experts, patient advocates, and caregivers to the individual patient themselves having a better understanding about their personal health.

Drive Health Equity with foundation models trained on inclusive world data from diverse groups for more trustworthy and equitable information.

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