At the Portfolio Private Health 2026 conference, Kriller Norbert, co-founder and CEO of XMED360, and Mikó Botond, CEO of XEENIA, outlined platform concepts intended not just to support healthcare IT processes, but to create ecosystems that track a patient’s whole journey, involve employers and other companies, and assist clinicians with artificial intelligence.
XMED360: an ecosystem tying clinical care to enterprise functions
Kriller Norbert emphasized that XMED360 should not be seen merely as a medical software product. He compared the approach to Apple’s ecosystem: an iPhone alone is a device, but its power comes from the interconnected services. Similarly, XMED360 seeks to connect different care processes in a single system. The platform handles multiple care settings — from outpatient and inpatient care to day surgery — while also integrating enterprise resource functions such as controlling, quality management, inventory management, CRM and sales processes.
Kriller highlighted three priority areas where systems must deliver more: closer engagement of patients and companies, and the use of artificial intelligence.
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Preventing the patient from disappearing after the visit: one major problem today is that the clinician–patient relationship often breaks off once the appointment ends. XMED360’s goal is to digitally interpret what was discussed during the encounter and convert clinician instructions into follow-up processes, for example by sending reminders when a medication or action is due.
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Motivation through gamification: Kriller cited language-learning apps (for example Duolingo) as examples of how to keep users engaged over long periods. He argued similar motivational techniques can be applied in healthcare; XMED360 incorporates gamification and loyalty features to encourage adherence to therapies.
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Integrating corporate health programs: currently employers and healthcare providers often connect through separate collaborations. XMED360 envisions a single system with access layers that would allow the healthcare provider, employer and employee to participate in unified processes.
The ecosystem is also designed to handle cases where a prescribed therapy or lifestyle change requires purchasing a product, such as supplements, a smartwatch or exercise equipment.
XEENIA: an AI stack for normalization, semantic interpretation and automation
Mikó Botond presented XEENIA’s technological approach, saying the development focuses on two fundamental goals: increasing efficiency and improving quality. The XEENIA system is built on three main layers: perception of information, understanding and interpretation, and evaluation.
The platform can automate parts of the patient pathway at various points and support healthcare professionals. Mikó stressed that for medical applications, controllability of the technology and data governance are particularly important: the system runs on its own infrastructure, patient data are kept under control, and the developers use their own models and clinical interpretation modules.
A key element is lab data harmonization: because different laboratories may use diverse names and structures for the same test, the system normalizes results to international standards so they become comparable.
At the core of the development is a semantic engine tasked with content-level interpretation of medical texts. Mikó argued this is an area where many current healthcare AI solutions are lacking. XEENIA connects multiple international medical coding systems and knowledge bases so it can do more than detect keywords or documents — it seeks to understand relationships among the medical facts contained in them.
Depending on integration, the technology can be used to augment clinician consultations, process laboratory results and professionally support, for example, insurance workflows. Outputs are displayed on a medical dashboard: the system can compile a disease timeline from prior documents, summarize records, highlight current therapies, allergies and chronic conditions, and — if integrated — show vital parameters.
Documentation automation and future aims
The developers have also built an ambulatory-note generator that can listen to the full conversation between clinician and patient, link that to available documents and lab results, and draft the ambulatory documentation. This can remove the need for clinicians to dictate or type documents separately.
In the longer term, and given the proper regulatory and legal framework, the teams aim for the system to offer deeper diagnostic support to clinicians.
Conclusion
Both presentations at Portfolio Private Health 2026 reflect a shift from siloed documents and discrete administrative tools toward integrated, interpretable health data and workflows. XMED360 emphasizes patient and employer engagement and business process integration with motivational elements, while XEENIA focuses on data normalization, semantic interpretation and AI-driven automation to improve efficiency and quality.
