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Editorial Advisory Board

  • Professor Andrea M. Armani, University of Southern California
  • Ruti Ben-Shlomi, Ph.D., LightSolver
  • James Butler, Ph.D., Hamamatsu
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  • Justin Sigley, Ph.D., AmeriCOM
  • Professor Birgit Stiller, Max Planck Institute for the Science of Light, and Leibniz University of Hannover
  • Professor Stephen Sweeney, University of Glasgow
  • Mohan Wang, Ph.D., University of Oxford
  • Professor Xuchen Wang, Harbin Engineering University
  • Professor Stefan Witte, Delft University of Technology

Visolyr and HITLAB Partner to Advance AI Solutions for Women’s Health and Cardiometabolic Disease

(PRUnderground) May 27th, 2025

Visolyr, a digital health platform focused on AI-powered clinical solutions, has partnered with HITLAB, a leading health innovation research lab, to accelerate the development and validation of a breakthrough Generative AI platform designed to transform healthcare delivery.

Under a strategic services agreement, HITLAB will support Visolyr in building and refining its Generative and Agentic AI platform for healthcare through rigorous validation research, publication, business model development, investor engagement, and strategic partnerships. The collaboration aims to bring to market a clinically validated solution that improves clinical documentation, enhances decision support, elevates patient engagement and education, and strengthens medication management.

Visolyr’s AI platform is engineered to accelerate digital health transformation by integrating Generative AI, AI agents, and intelligent automation directly into clinical workflows. With a focus on women’s health and high-burden conditions such as cardiometabolic diabetes—particularly in patients with kidney disease and hypertension—Visolyr delivers personalized, proactive, and coordinated care. The platform enables enterprise-wide AI deployments that enhance clinician efficiency and improve patient experiences at the point of care.

Through its participation in the NVIDIA Inception program, Visolyr has deployed NVIDIA Inference Microservices (NIM) to deliver sub-second, context-aware AI responses. This has powered Visolyr’s latest demo capabilities, which include hybrid AI workflows, Retrieval-Augmented Generation (RAG) automation, and optimized routing.

“HITLAB is committed to accelerating the adoption of impactful technologies that address unmet healthcare needs,” said Dr. Stan Kachnowski, Chair of HITLAB. “Our collaboration with Visolyr reflects our shared vision of using cutting-edge AI to streamline clinical processes, improve outcomes, and reduce costs.”

Visolyr Founder and CEO Michael Joseph added, “Our partnership with HITLAB is a critical milestone in our mission to bring context-aware AI to the point of care. Together, we are advancing a platform that not only empowers clinicians but also personalizes the care journey for patients.”

HITLAB, known for initiatives such as the HITLAB World Cup, Women’s Health Tech Initiative, and Breakthrough Alliance, will also help position Visolyr’s innovation within the broader healthcare ecosystem through seminars, conferences, and thought leadership.

About Visolyr
Visolyr is a healthcare AI platform that enables enterprise-scale deployment of Generative AI and intelligent agents within clinical workflows. Focused on enhancing clinical decision-making and streamlining care for complex chronic conditions, Visolyr is on a mission to improve health outcomes, provider productivity and operational efficiency through next-generation technology at the forefront of AI innovation.

About HITLAB

HITLAB is an impact-first organization that offers digital health research, teaching, and advisory services to improve health delivery around the world.

At HITLAB, we believe technology and health can work together to improve the quality of health delivery and healthcare worldwide. We use rigorous research and evidence-based methods to identify the best digital health solutions for each of our partners.

The post Visolyr and HITLAB Partner to Advance AI Solutions for Women’s Health and Cardiometabolic Disease first appeared on

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