Dear readers,

This week, we look at a theme that still feels surprisingly underexplored across Southeast Europe: longevity. While Silicon Valley is pouring billions into extending human healthspan, in SEE the movement is only beginning to take shape through startups working on everything from epigenetics and AI to nutrition hardware and pet wellbeing. 

At the same time, the region’s startup ecosystem continues to adjust to a tougher market reality. With capital still scarce and fundraising cycles longer, founders are shifting away from aggressive growth toward sustainability, efficiency, and survival. This is also reshaping how companies are built across SEE, from product strategy to hiring and expansion.

The past week also brought new signals of resilience, from investment activity in Greek AI startup Norma and acquisition momentum around Croatia’s Irundo, to Macedonia-founded EmbedSocial crossing 400,000 users globally. And in our founder interview, we highlight a key shift in today’s startup reality: for many, the main constraint is no longer capital, but execution under pressure.

Enjoy the read!
Bojan Stojkovski
Editor-in-Chief, IT Logs

The idea of longevity in SEE is still in its early phase of discovery and popularisation, as health has traditionally been reactive - something addressed after decline rather than continuously managed. 

Thus, for the time being, the concept of longevity exists in fragments, with different pieces emerging independently across the region: from biotech laboratories in Bulgaria working on biological age and epigenetic signals, to hardware startups in Greece experimenting with food and metabolic tracking, and pet-tech initiatives in Serbia exploring how animal behaviour can be quantified and interpreted.

What is still missing is cohesion between these efforts, or a shared institutional backbone that would typically connect such developments into a defined ecosystem. Instead, what is visible are small and focused attempts to translate aspects of life that were once considered subjective or unmeasurable into structured data. What connects such efforts though, is a shared intuition that aging, health, and even emotional wellbeing can be measured, modelled, and gradually improved through data.

Turning biological age into a signal

In Bulgaria, Epix AI is working at the most abstract end of this emerging stack: biological ageing itself.

Their approach starts from epigenetics, one of the more complex branches of modern biology, and attempts to translate it into something operational. The company’s aim is to estimate biological age with higher precision and turn it into a dynamic indicator rather than a static number.

That notion shifts longevity away from long-term prediction and toward continuous observation. In their model, health is not something assessed once a year in a clinic, but rather something updated, recalculated, and tracked over time.

The underlying ambition is to “revolutionize healthcare by harnessing the power of epigenetics to provide individuals with personalized, dynamic health scores.” It is a language closer to software than medicine, but the implications are clearly biomedical: if aging can be measured more precisely, then it can also be intervened in earlier.

The kitchen as a longevity device

If Epix AI is operating at the molecular layer, Qalzy is working at the level of everyday behaviour - specifically, what people eat. 

At first glance, Qalzy is a hardware startup building an AI-powered kitchen scale. But its positioning increasingly overlaps with the broader longevity conversation: nutrition as a measurable determinant of long-term health.

He breaks this down into two dominant groups shaping demand.

The second group is more tied to life stage than culture. “The other group is our generation, people who are now entering their 40s. At that stage, a lot of people start to realize that age-related decline is inevitable, and that’s often when they begin to think more seriously about it.”

He contrasts this with earlier decades of life, where long-term thinking is often deprioritised. “In your 20s and 30s, you might enjoy life more freely - partying, indulging in pleasures, not thinking too much about long-term consequences. But then you reach a point where you start thinking, I need to be more careful now.”

And ultimately, the shift is not conceptual but physical. “It becomes less about abstract ideas and more about how you actually feel day to day.”

Koukoravas describes the origin of Qalzy in similarly personal terms. “During COVID, putting on some weight suddenly spiked the interest in longevity,” he says. 

What followed was a familiar cycle of calorie tracking and nutritional logging, but it quickly revealed a structural problem. “It is very time consuming, because every time you have to weigh something and then write it on your phone,” he explains.

That gap became the design constraint behind Qalzy: a kitchen scale with a retractable camera that identifies and weighs food automatically, removing the need for manual tracking.

Thus, the principle behind it is simple: “You cannot improve what you cannot measure.” Koukoravas points out.

Extending measurement beyond humans

In Serbia, WellPet.ai extends this logic into a different domain entirely: pet wellbeing.

The company builds AI and IoT systems that interpret dog behaviour through movement, vocalisation, and behavioural patterns, translating them into actionable insights for owners.

Founder Nikola Milanovic describes the company’s evolution as shaped by early setbacks and reflection. “We failed in few things, and we had a few problems,” he says, recalling earlier attempts to scale a software product that reached users but did not achieve sustainable growth.

That failure triggered a reset in approach. “We just sit down and create a meeting and talk, okay, what is the experience? Why did we fail?” he explains. From there, the company shifted toward more structured validation and external input.

The result is WellPet.ai, built around the idea that dogs’ emotional and physical states can be inferred through behavioural data if properly collected and interpreted.

That relationship is also reciprocal. “Their wellbeing is also closely tied to our own. How we feel often affects them, and they can sense it.”

Ultimately, the system is designed around shared optimisation. “We’re designing systems that consider both sides: the dog’s happiness and health, and the human’s wellbeing. When your dog is healthy and happy, you tend to be healthier and happier too, and it reinforces a positive feedback loop that improves both lives.” Milanovic concludes.

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