Professor Gulnur Kalimuldina of Nazarbayev University is one of the first scientists in Kazakhstan to turn laboratory research into a DeepTech startup. It all began with experiments on materials capable of generating electricity from movement. This idea led to the launch of Mirai Tech. The startup is developing smart nano insoles that analyze athletes’ movements and help detect injury risks before doctors can spot them. Today, Mirai Tech’s technology is being tested by football clubs in Kazakhstan, and the team has already secured $90,000 in investment.
For the joint project by Digital Business and Astana Hub, 100 Startup Stories of Kazakhstan, Gulnur shared how shoe sensors can help sports clubs save millions of dollars — and when Mirai Tech’s insoles will become available to the general public. She also revealed when the project is expected to reach $100,000 in profit, which foreign markets it plans to enter, and where the team aims to launch mass production.
«In just two minutes, the insole collects over 20,000 data points»
— Mirai Tech grew out of scientific research. When did you first realize that the idea had the potential to become a full-scale startup?
— The idea to launch a startup came while we were researching materials that could generate electricity from movement. At some point, we noticed that the sensors didn’t just produce electrical current. They also reacted differently depending on how a person walked. That’s when we realized this could become real technology with practical benefits.This is how the concept of smart nano insoles was born. These are insoles equipped with sensors based on nanogenerators, which detect even the slightest movements and pressure. The word “nano” in the name reflects the nanotechnologies that started it all.
At first, we explored several directions, including rehabilitation for Paralympic athletes and tracking motor development in children with autism. However, we eventually decided to focus entirely on sports. We registered the company in January and concentrated our efforts on SportTech. These are technologies designed to help athletes train and recover using data and artificial intelligence.
— What made you choose sports as your main focus?
— We saw strong interest from professional sports clubs, especially in team sports. In football, hockey, or basketball, an injury doesn’t just mean a break from training—it also leads to serious financial losses, including treatment, recovery, and finding replacements. In top-tier leagues, these situations can cost millions of dollars.
In Kazakhstan, there’s a serious shortage of qualified rehabilitation specialists who can detect issues early on. Our nano insole essentially takes on that role of early diagnostics. An athlete walks for just two minutes, and we can immediately identify asymmetry, overpressure, and improper weight distribution. This data helps doctors and coaches better understand the root of the problem and how to adjust the load accordingly.
— How do the nano insoles work, and what kind of data do they collect?
— We integrate sensors into the insoles that capture even the slightest human movements. They track how the foot lands, where body weight shifts, and how pressure is distributed during walking, running, or jumping. The sensors are sensitive enough to detect even micro-movements. In just two minutes, the device collects over 20,000 data points, which are then processed using our proprietary algorithms. This is how we create a digital movement profile for each user.
We also use additional wearable sensors placed on the athlete’s body. These capture joint angles, detect imbalances, and identify deviations in movement technique. For example, a coach might notice a drop in a player’s performance but not understand the cause. Sensor data helps pinpoint the exact issue, whether it’s asymmetry in movement, incorrect technique, or hidden strain.
— What was the system trained on? Every person has a unique walking style, posture, and movement pattern. How does the algorithm distinguish between individual traits and actual warning signs?
— The system is built on mathematical models—algorithms that interpret human movement and analyze micro-signals collected from the sensors. Each step and each pressure point forms a unique pattern. By recognizing these patterns, the system can distinguish between natural, physiological movement and potential issues that fall outside the norm.
To train the system to recognize differences, we built a large anonymized database. We tested the technology in nine hospitals across Astana, as well as in several sports centers. The data includes a wide range of movement patterns, both from individuals with injuries and those without.
Using this data, we calibrate the system, improve its accuracy, and continuously train it to recognize movement patterns. At its core, this is more than just a set of sensors — it’s an analytical model that understands when the body is functioning properly and when it may need support.
— How is the data presented to the coach?
— All information is presented in a clear and easy-to-understand format. Coaches can view key parameters such as asymmetry, load distribution, and recovery dynamics. If they have questions about how to translate this data into a training plan, our in-house rehabilitation specialists step in to help. Right now, we don’t have a large number of clients, which allows us to work individually with each one. But as we scale, we plan to introduce an AI model — currently in training using anonymized clinical and research data — that will assist in interpreting results.
«In Europe, we’ve been told that they’ve never seen this level of detail in analytics»
— Where have you already tested the technology?
— We ran a pilot project with the football club Astana. Over the course of a month, we identified hidden issues among players, helped adjust their training loads, and suggested changes to their training plans. After the pilot, we trained the team to use the system independently, and we’re now discussing the possibility of signing a one-year contract.
We also worked with FC Tobol from Kostanay, one of the top teams in the Kazakh Premier League. We conducted a one-time diagnostic session to assess the players’ condition and the load on their joints. Now, we’re preparing for another session with the team.
We arranged an on-site diagnostic check-up and carried it out with our team. This format turned out to be very convenient for the club. After this first paid collaboration, we plan to discuss a one-year contract. The negotiations coincided with a tight match schedule, so the final decision is still in progress.
— Can you share the details of your business model? How does the company generate revenue?
— We offer two main options. The first is technology sales: the client purchases the system and pays a subscription fee for access to analytics. The package also includes training in sports rehabilitation, as well as guidance on how to interpret the data and integrate it into the training process.
The second option is diagnostics carried out by our team. This is offered as a check-up format. A club can purchase an annual program, and we visit them once every three months
By the beginning of next year, we expect to reach a quarterly profit of around $100,000.
— Will this profit come mainly from Kazakh football clubs, or are you planning to expand into international markets as well?
— Of course, we expect the main growth to come from international markets. We’re currently starting negotiations with five European football clubs and plan to conduct pilot tests with them, aiming to sign agreements afterward. To support this, we’re working on improving the product so it looks and functions like a finished, market-ready device, not just a lab prototype.
— Major football clubs can afford the most advanced and expensive technologies. What makes them choose your solution?
—There are several companies on the market producing sensor-equipped insoles, but our technology stands out by capturing the slightest changes in movement, those that can’t be seen with the naked eye. In Europe, we’ve been told that they’ve never encountered this level of detail in movement analytics before.
In most cases, this type of diagnostics is only available in specialized clinics, and the process is often complex. An athlete has to come in, get connected to multiple sensors, be recorded on camera, and then receive a lengthy report full of graphs that are difficult to interpret without expert help. We simplify all of that with one compact device and clear, easy-to-understand analytics.
«We’re currently in negotiations for a pre-seed funding round of over $500,000»
— What kind of funding did you use to develop the project in the beginning, and how much have you raised so far?
— In the beginning, the project was funded mostly with my personal savings. We also received partial support through research grants. Jas Ventures Limited was the first to believe in us, investing $90,000 as part of a bridge round. They see strong potential in the technology and plan to participate in future rounds as well. Currently, we’re in negotiations for a pre-seed round of over $500,000. In addition, we recently won $25,000 at the Astana Hub Startup Battle hosted by MA7 Ventures, and secured a grant of 10 million tenge in the finals of the national AI SANA Generative Nation competition.
— What will the new funding be used for?
— The funding will be used for scaling and launching mass production. Right now, we assemble the device manually in our lab, which works for pilot projects but isn’t suitable for fulfilling larger contracts. We simply can’t produce large volumes of insoles on our own. To meet growing demand, we plan to outsource part of the production. The sensor technology and electronics will remain in-house, but components like the insole body or certain modules can be manufactured externally, most likely in China.
In addition, part of the funding will go toward patents, R&D, and enhancing the AI analytics, which will become the core of the system. Our goal is for Mirai Tech to evolve beyond just a device that collects movement data. We aim to build a full ecosystem for injury prevention across various sports.
— So does that mean you plan to expand beyond football?
— Yes, we plan to expand into basketball next, including entering the NBA market in the United States, which represents a huge opportunity. After that, we’re targeting hockey and tennis. We also see strong potential in working with youth academies and sports schools, where it’s possible to instill proper movement techniques early, at the stage when athletes are just beginning to develop their biomechanics.
We also plan to make the technology accessible not just to professional athletes, but to a broader audience. By the end of 2026, we aim to make Mirai Tech’s smart nano insoles available for anyone to purchase. Even if you’re not a professional athlete — whether you go to the gym, enjoy regular fitness activities, or are training for an amateur running marathon — it’s important to track your movement dynamics and avoid overloading your knees and back. Our analytics will help users understand whether they’re stepping correctly and if there are any early signs of injury.
—You now have very clear goals, but just a year ago you mentioned that, coming from a scientific background, you lacked business experience. What helped you adapt and catch up so quickly?
— We took part in the ABC business incubation program by NURIS last year, and more recently in the Silkway Accelerator by Astana Hub and Google for Startups. Over those three months, we completely reworked the product to better reflect its value for clients and focused on building a sales strategy. My mindset also shifted. I began to see the project not as a scientific experiment, but as a tech-driven business. The team played a big role in that transformation. We were joined by Asset Begaliyev, our Business Development Director, who has experience in launching startups, and Azamat Eszhanov, our Operations Director, who now oversees our business processes.
— But is the scientific side of the project still your responsibility?
— From the very beginning, the scientific part of the project has been and still is my responsibility. I’m a research scientist, and I oversee everything related to next-generation sensors, data analysis, experimentation, and hypothesis testing. This scientific foundation is what our startup is built on. We didn’t just assemble a device. We developed a technology rooted in a deep scientific approach. Together with our engineering team, we continue to strengthen and expand this direction.
We’ve brought strong experts onto the team, including a CTO for both technology and machine learning. Our Hardware CTO, Manat Nursultan, is responsible for the system architecture — from circuit design and technical layout of the sensor modules to scaling the solution for production. He and his team focus on developing and optimizing high-sensitivity sensor elements and energy-efficient microcontrollers, ensuring the device functions reliably and with high accuracy.
Our ML CTO, Abylaikhan Ergesh, leads research in machine learning and biomechanics in close collaboration with the rehabilitation and trauma specialists on our team. His work focuses on processing and interpreting data streams, developing robust models that can recognize movement patterns, analyze load distribution, joint angles, micro muscle reactions, and the body’s response speed. Thanks to his approach, the system is being trained to detect insights that regular wearable devices simply don’t capture.
— What goals have you set for yourself and your team in the coming years?
— By the end of 2026, we plan for Mirai Tech to reach a valuation of around $100 million. In two to three years, I see it becoming an international company, standing alongside the biggest names in the sports industry. Picture a match between Real Madrid and Barcelona, with thousands of fans watching around the world — and our logo appears in the stadium. That’s the kind of moment I’m working toward. That’s when I’ll know: our team truly made it.