There is a particular kind of restlessness that belongs to people who cannot stop asking what is happening beneath the surface of things. It shows up in scientists staring at data until a pattern finally speaks, in writers rereading a paragraph until it tells the truth, and, as it turns out, in entrepreneurs who spend years fasting and exercising simply to notice, with almost scientific patience, how the body responds. For Andrey Bukayev, that curiosity began long before boardrooms, patents, or the word “startup” ever entered the picture.
Andrey Bukayev is the Founder and Chief Executive Officer of ProRegion Corporation, a U.S. registered health tech company working at the intersection of wellness, medical technology, and artificial intelligence. But to understand what he is building now – a modular ecosystem of blood analysis devices, biometric smart toilets, and digital lifestyle assistants – it helps to go back to something much smaller and much more personal: his own effort to understand how the body responds to changes in diet, activity, and lifestyle.
A Curiosity That Started With Fasting
“My interest in preventive health began long before I considered creating a technology company,” Andrey says. For many years, he periodically practiced 24-hour fasting and exercised, alternating between different routines. Over time, he noticed changes in his energy and physical performance and began asking what was happening inside the body when diet, activity, and lifestyle changed. That curiosity gradually developed into an interest in physiology, longevity, and objectively tracking changes in the body over time.
The Gap Between a Number and an Understanding
In recent years, as Andrey began searching for technologies that could offer more objective health monitoring at home, he ran into a challenge that many people face. Numbers alone, he realized, are not enough. For someone without medical training, terms like hemoglobin, CRP, and iron can remain unfamiliar. A single biomarker can be explained on its own, but the larger picture, the relationships between markers, and the trends across time are harder to understand.
That gap is where he saw an opening. “Advances in AI and data processing suggested a way to connect measurement history and different types of information within one understandable ecosystem,” he explains. The goal is not simply to generate more measurements, but to connect them in a way that makes the overall picture easier to understand.
Why Blood Came First
Blood became a natural starting point because blood testing can provide information about many physiological processes through measurable biomarkers. He became interested in whether such observations could be made more regularly and conveniently at home, without requiring a trip to a facility every time. That curiosity became HemoIntelix, a home-based blood analysis concept designed around a simple principle.
The idea is to use the minimum necessary sample, automate selected measurements, and help users see trends rather than isolated results. A home-based format, Andrey notes, can reduce dependence on facility visits, while non-invasive approaches remain, in his view, an important direction for the future, although those approaches are not yet the focus of the current system.
AI as a Translator, Not a Doctor
Ask Andrey where artificial intelligence fits into all of this, and he draws a boundary immediately, one he returns to throughout the conversation. “I view AI not as a replacement for physicians, but as a tool for working with a complex history of data,” he says. Its real value emerges when several biomarkers, a person’s baseline, and changes over time all need to be considered together.
But he is equally clear-eyed about AI’s limitations. Inaccurate or incomparable measurements do not become useful simply because there are many of them. Models, in his framing, must be trained, tested, and improved with experience. And serious medical decisions, he insists, still require professional evaluation.
The Bathroom as an Overlooked Frontier
If HemoIntelix represents the blood-centered arm of the ecosystem, the modular smart toilet system represents something almost accidental in its origin. It began, Andrey explains, as a simple hygiene question: what happens when several people share the same bathroom? But the question evolved. It became clear that reliable user identification could support something larger: personalized, passive monitoring.
Urine, stool, and other biological materials, he points out, may contain useful information that is normally lost during everyday routines. The opportunity is to collect selected data naturally, without requiring a person to constantly wear a device or initiate a separate procedure. He is careful to note that the technical implementation is still evolving and will require careful validation, a caveat that runs through much of the ecosystem’s newer components.
Connecting the Dots: Biology, Behavior, and Environment
A single measurement, Andrey says, rarely provides the full picture. His approach is to consider biomarkers alongside physical activity, nutrition, daily routines, weight, environmental conditions, and other available information, treating these inputs as interconnected rather than isolated. The platform, as he envisions it, could even ask follow-up questions when it detects a meaningful change, adding context to what the data show rather than leaving the user with a single number.
Individual biomarkers, he explains, can be organized into thematic groups and higher analytical levels, helping people see overall dynamics rather than fixating on one figure in isolation. “As high-quality data accumulate, AI may identify relationships,” he says, “but those patterns still need to be tested against real observations.” That emphasis on validation is central to his approach to using AI in preventive health.
SolarTime and the Rhythms Nobody Tracks
Perhaps the most unexpected piece of the ecosystem is SolarTime, a time system tied not to the clock on the wall but to the actual duration of daylight and darkness at a specific location, including sunrise, sunset, and seasonal changes treated as potential context rather than background noise. Andrey is refreshingly honest about where this idea currently stands. “I do not consider SolarTime to have a proven medical effect,” he says plainly. At this stage, it remains a research variable, one that future data will need to validate before anyone can say whether light cycles, personal routines, and biological measurements are truly connected.
It is a small but telling detail about how he operates: an idea can be worth exploring while still remaining explicitly unproven.
Trust, Before the Data Even Arrives
For a company built around personal health information, trust is not an abstraction; it is infrastructure. Andrey describes trust as something that begins before data ever reaches an AI system. It starts with protecting the integrity of the sampling process itself, including reducing contamination, avoiding mix-ups, and ensuring accurate association between a sample and its user. Hygiene, cleaning, and precise identification matter across every device in the ecosystem, not as an afterthought but as a first principle.
Beyond the physical process, he emphasizes that users should always understand what is being collected, where it is stored, and who can access it, and that they should retain the choice of whether to share their results with a physician or telemedicine service. Any research use of de-identified data, he adds, should include appropriate consent and safeguards.
Where the Line Is Drawn
Andrey draws a clear distinction between collecting and analyzing information and making an actual medical decision. A system, in his view, can automate parts of data collection, combine results, track changes over time, and make complex information easier to understand. But diagnosis and treatment decisions, he insists, should remain with qualified medical professionals, while the user retains control over personal data.
“AI may highlight a change or trend, but it should not create an illusion of certainty,” he says, a line that captures much of his philosophy in a single breath. The future he describes is not one where AI replaces the doctor’s office, but one built on cooperation among AI, the user, and relevant medical specialists, each playing a distinct and necessary role.
One Founder, Many Disciplines
At this stage, Andrey describes his own role with unusual candor. His job, as he sees it, is to shape the overall architecture, define how the various technologies interact, and develop the intellectual property behind the ecosystem. He is quick to acknowledge what he cannot do alone. “One person cannot be an expert simultaneously in biotechnology, AI, software, hardware, and medicine,” he says.
The next stage, he explains, requires funding, prototypes, and a genuinely interdisciplinary team. One priority moving forward is bringing in a strong technical or project leader, someone capable of identifying the necessary expertise and assembling specialists around specific stages of development, so that the ecosystem can move from architecture toward practical execution.
The Road Ahead: Three Years, Five Years, Ten Years
Andrey’s timeline for the next several years centers on funding, team formation, and the development and testing of initial prototypes, the essential groundwork beneath any ambitious technology. With successful development, he would like to see the first solutions reach the market within roughly three to five years, while acknowledging that research and regulatory requirements will inevitably shape that timing.
The next major task after that, he says, is generating high-quality real-world data and building a longitudinal history, the kind of long-term dataset that gives AI something meaningful to learn from. Looking further out, within ten years, he hopes to see a mature ecosystem, one with practical experience behind it and a data foundation substantial enough to support deeper analysis.
What Has Already Been Built
Ask Andrey what he considers the most important achievement so far, and he does not point to a product launch or a headline. He points instead to something quieter: the formation of a coherent technology architecture and the protection of intellectual property across the ecosystem’s key directions. The process of protecting that intellectual property through U.S. patent filings, he confirms, is currently underway.
Alongside that, the analytical logic behind the ecosystem continues to take shape. Biomarkers, he explains, can be considered separately, but they are also being organized into thematic groups and higher analytical levels, designed to track broader dynamics relative to a person’s individual baseline. He is careful, as always, to note that these approaches still require real-world data and validation before they can be considered proven. The next stage, in his own words, remains funding, team building, prototypes, and experimental validation.
What emerges from a conversation with Andrey Bukayev is not the portrait of a founder chasing hype, but of someone building, piece by careful piece, a system intended to make complex health information more understandable while recognizing the limits of what emerging technology can currently prove.
Quotes
