If you believe AI is merely a bubble, or irrelevant to humanity’s deepest and most fundamental challenges, prepare to reconsider. When cutting-edge AI meets Nobel Prize-winning economic theory and one of humanity’s most important goals after survival, the world does not simply change, it is transformed for ever. The real question is who will recognise that opportunity early enough to help shape it and benefit from its growth. If you are an investor and are interested in what we are doing, feel free to contact us or/and download our Stable-Match presentation to discover the investment opportunity. Additionally, you can visit our minimum viable product here. You can watch conceptually what the MVP does in the below video which was our first beta under the name of Oolalaaa.
Game-theoretic AI represents a major untapped business opportunity and lies at the heart of what we call Cognizant Social Engineering, the concept represented by the “C” in EQRC. Its purpose is to design intelligent systems that improve how individuals, businesses and institutions are matched with one another. Matching theory has already demonstrated its value in highly structured environments, including the allocation of medical graduates to hospitals and students to schools. The research associated with these mechanisms contributed to Nobel Prize-winning work in economics. Yet dating remains one of the largest and least effectively designed matching markets. Most dating platforms rely on superficial filters, individual recommendations and repeated swiping. They attempt to predict whom a user may like, but rarely consider the preferences, alternatives and strategic choices of all participants at the same time. This creates inefficient matches, excessive competition for the same profiles, hidden incompatibilities and a poor user experience. By combining artificial intelligence with stable-matching mechanisms, dating platforms can move beyond simple recommendation engines. They can learn complex preferences, account for mutual compatibility and identify the best realistically achievable match for each user within the wider network. The same principles can also be applied to recruitment, lending, procurement, advertising, logistics and digital marketplaces. Rather than merely predicting individual behaviour, Cognizant Social Engineering seeks to optimise interactions across entire systems, producing outcomes that are more efficient, stable and valuable for everyone involved.
History of the Project
The project’s first beta version was launched under the name “Oolalaaa.” The choice of name had both a personal and a commercial origin. On a personal level, “Oolala” began as an inside joke among a group of friends. From a branding perspective, the name was also influenced by the perceived popularity among venture capital investors of technology companies with double letters or repeated vowels, such as Google, Yahoo, Zoopla and Zoosk.
In retrospect, the name proved to be a poor strategic choice. “Oolala” was already in use, which required us to add three additional letters to secure a distinctive name and domain. This made the brand more difficult to pronounce, remember and position. The situation became more problematic when an unrelated and inappropriate website began operating under a similar name, creating an unacceptable risk of confusion and reputational damage.
The original project was entirely financed from the founder’s personal income, which imposed strict limitations on the development budget. To control costs, a group of freelance engineers based in India was initially hired. Unfortunately, the development process was poorly coordinated, and previously resolved bugs were repeatedly reintroduced into the platform. As a result, the product never reached the level of technical stability required for a successful public launch.
Several smaller venture capital firms approached the project during this period. However, the proposed investments and valuations were not sufficient to finance the redevelopment needed to give Oolalaaa a realistic chance of success. Rather than accepting external capital for a product that had lost momentum and still faced significant technical challenges, we decided to pause the project and focus on rebuilding its foundations.
The concept was revived in 2026 under the new name Stable Match. This time, the project was developed through a smaller and more tightly structured team, with key responsibilities assigned to trusted collaborators whose incentives were directly aligned with the long-term success of the business.
The first web-based Minimum Viable Product was deployed in July 2026. Native applications for Apple iOS and Android are currently under development. The platform is initially being tested within a limited circle of users, allowing us to gather feedback, identify technical issues and refine the user experience before a broader launch.
We expect to begin considering external investment from September 2026 onwards. Any investment would be used to strengthen the engineering team, accelerate mobile development, support user acquisition and prepare the platform for wider commercial deployment.
About the concept of Stable Matching
In mathematics, economics, and computer science, the stable marriage problem (also stable matching problem or SMP) is the problem of finding a stable matching between two equally sized sets of elements given an ordering of preferences for each element. A matching is a mapping from the elements of one set to the elements of the other set. A matching is stable whenever it is not the case that both the following conditions hold.
– There is an element A of the first matched set which prefers some given element B of the second matched set over the element to which A is already matched, and
– B also prefers A over the element to which B is already matched.
About the Princess Dilemma
The princess dilemma also known as the secretary problem is a famous problem of optimal stopping theory. We have designed a simple video to illustrate the concept here.
“This thing is absolutely genius”
– Hugo and Goli