In October 2025, we launched the AI/UX Lab—a laboratory combining user experience research and the exploration of opportunities to implement artificial intelligence in digital products. On its basis, companies can test hypotheses, check interface usability, and explore AI integration possibilities to improve user experience.
As part of the pilot launch at MOST IT Hub, we held research meetups, an eye-tracking equipment demonstration, workshops, and testing with IT hub residents, shaping a new data-driven development culture in the region.
You can read about the lab's launch and its presentation to the Akim of Almaty in Forbes Kazakhstan.
What the AI/UX Lab is
The laboratory is a centre of expertise and experimentation that brings together UX research, data analysis, and the development of experimental solutions, both in terms of user experience and conceptual novelty based on new technologies, particularly AI. Here, companies can test their services, interfaces, and models before going to market, verifying their efficiency, usability, and ethical correctness. Or they can invent entirely new products.
The AI/UX Lab is a place where technology and humans meet before release to make products more accurate, understandable, and secure.
The laboratory is particularly relevant for:
- mass-market products, where a mistake can cost millions and undermine user trust;
- banks, fintechs, and digital platforms, where thousands of clients interact with interfaces and AI systems daily;
- companies striving to implement an evidence-based approach to development;
- products and companies operating in a highly competitive market, where finding solutions to stay ahead of competitors is required.
Why we launched the AI/UX Lab and why the market needs it
Today, simply releasing a digital product is not enough. For it to be in demand, you need to understand in advance whether users have a real need, what the market demand is, and how strong the competition is. To do this, companies test hypotheses, study audience behaviour, and evaluate the product's potential before investing in development. This approach reduces the risk of making a mistake and allows launching solutions backed by data, not intuition.
For existing products, the tasks are different. In mature markets, it is critical to find growth points, understand why users choose a particular scenario, and see where they hit barriers. Research helps uncover real needs, increase conversions and retention, and find elements that can become differentiators. This directly impacts the efficiency of a digital business.
We launched the AI/UX Lab to help companies solve these tasks systematically. The laboratory allows for quickly testing hypotheses, validating new products, identifying growth areas in existing services, and making fact-based decisions. We do this together with clients and partners while simultaneously helping the market build a culture of regular digital product research.
How the AI/UX Lab works
In the laboratory, teams can observe user behaviour live and obtain objective data on how the product works. The research process is structured to capture real reactions and simplify the path from hypothesis to solution.
Every project begins with posing questions: what exactly needs to be tested in the product and what business risks are important to mitigate. For this, specific scenarios and hypotheses are formed:
- how a user opens a deposit;
- how they find bank details;
- how they make a card-to-card transfer;
- whether they understand the logic of tariffs and commissions.
Preparing the scenario and research tasks
After this, the team prepares a research protocol, selects respondents, sets up the equipment, and creates observation checklists.
Immersing the user in a real scenario
The main part of the laboratory is a closed research area. It houses:
- Testing room — here the respondent works with a moderator. They perform tasks in the most natural environment possible: at a laptop or phone, exactly as they would at home or work.
- Observation room — a team of researchers, designers, analysts, and product managers monitors what is happening through a one-way Gesell mirror or a video broadcast system.
In the testing room, the respondent performs a task: "find the transfer fee," "open a new account," and speaks their actions aloud. The moderator unobtrusively asks clarifying questions if the user encounters difficulties.
The team in the observation room sees everything—from micro-expressions to behavioural patterns:
- where a person gets stuck;
- what causes distrust;
- what they search for too long;
- where mistakes are made;
- which interface elements are ignored.
Data collection and insight recording
Each session is recorded in multiple streams:
- the user's screen,
- face and gestures,
- the moderator's comments,
- the research team's observations.
Researchers record moments that cause confusion, double-check hypotheses, and note unexpected turning points in behaviour. Sometimes one short comment, like "I thought this button was inactive," becomes the key to a major insight. All this comes together into a detailed picture of how a person actually interacts with the product.
Analytics and final report generation
After a series of interviews, the team begins to collate the facts. At this stage, it is not individual episodes that matter, but patterns—recurring mistakes, identical pauses, similar user doubts.
Researchers combine observations, compare scenarios, and look for systemic bottlenecks. The result is a structural understanding of where and why a client might "stumble": which solution misleads the user, which phrasing makes them reread the text, and where the interface conflicts with a person's real expectations.
Following the research, the product team receives not abstract conclusions, but clear recommendations: what to change, how to simplify scenarios, where to rebuild the structure, and where to just rewrite the text. This allows for accelerating product development, increasing conversion, reducing the number of support requests, and avoiding costly mistakes during the development stage.
How to work with the AI/UX Lab
We are open to cooperation with friends, partners, and clients who need high-quality research for real product tasks. The laboratory will help quickly test hypotheses, test interfaces, analyze user behaviour, and find growth points for digital products.
In addition to research, we help companies launch their own research laboratories. The service includes setting up processes, training teams, and transferring expertise in AI and UX. This is critically important for large organizations where the quality of digital products directly affects business results and client loyalty. An internal laboratory can become a strategic asset providing a continuous cycle of evidence-based development.
You can learn more about the impact of research on digital products and discuss projects on the Rocket Tech Discovery department page.
