Traditional education follows a one-size-fits-all approach, despite students having different learning speeds, strengths, and weaknesses. As a result, students often practice skills they have already mastered, while struggling areas remain insufficiently addressed. Teachers also lack scalable tools to personalize learning for every student. To compensate, many families turn to private tutors, who are often expensive and not always aligned with the specific curriculum or learning goals. This leads to inefficient use of time, unequal access to support, and inconsistent learning outcomes. An affordable, adaptive solution is needed to personalize learning at scale.
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Driving students often repeat the same mistakes during lessons because feedback is mostly verbal and moment-based. After a lesson, students struggle to remember exactly what went wrong, when it happened, and why. Instructors also lack structured tools to document mistakes, track progress over time, and identify recurring patterns. This leads to inefficient learning, longer training periods, higher lesson costs, and increased stress for both students and instructors.
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The sports broadcasting industry faces a significant "commentary gap" for niche, amateur, and youth sports. While elite leagues enjoy high-production broadcasts, millions of smaller events such as regional volleyball, local cricket, or semi-pro soccer are streamed without any narration. This lack of play-by-play analysis makes broadcasts less engaging, harder to follow, and less shareable for fans and families. Human commentators are expensive and logistically difficult to deploy for every local game. Consequently, these sports struggle to build a loyal digital audience, as "silent" footage fails to capture the emotional stakes and tactical depth of the competition.
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Mathematics is widely regarded as one of the most challenging subjects in high school. There are several reasons for this, ranging from a shortage of qualified teaching staff to insufficient time dedicated to mastering diffucult core concepts. It is therefore no surprise that many students struggle with mathematics. We aim to change that.
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Research across Western Europe shows that healthy diets with fresh, minimally processed food are often more expensive than the typical diet based on processed products. This price difference affects lower-income households the most. At the same time, fast-food outlets are widely available in cities, while fresh and nutritious options are often harder to find and more expensive. This contributes to rising lifestyle-related diseases such as obesity and type 2 diabetes. The current food environment makes unhealthy choices the default for many consumers, particularly students and young professionals.
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Many bachelor and master students struggle to find relevant work that matches their studies and long term ambitions. A common problem is that students often end up in side jobs that have no connection to their education, while they could already be building relevant work experience. The main barrier is time. Students usually do not have enough time or access to the right network to find suitable study related jobs. Companies also find it difficult to reach and select the right academic talent efficiently.
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Many developers are “vibecoding” applications, which often leads to weak or overlooked security. This is especially common in React applications using Supabase, where misconfigured auth, database policies, and client-side logic can expose serious vulnerabilities. There is a clear need for a tool that helps developers identify, understand, and fix common security issues early, without slowing down their development workflow.
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Survey research has a usability problem. We're building Lensym, a survey research platform that fixes this. Not the kind of problem that shows up in user testing or heatmaps. The kind that surfaces three weeks into a longitudinal study, when you discover your branching logic doesn't work as intended. Or when you realize that collaborating with a colleague means emailing spreadsheets back and forth. Or when GDPR compliance requires you to manually pseudonymize data before export.
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Most small to mid-sized companies lack dedicated data analysts and optimization engineers, leading to inefficient decision-making in high-frequency operational processes. Traditional solutions like hiring consultants or full-time specialists are prohibitively expensive, leaving businesses running on intuition rather than data-driven optimization. Critical processes, from inventory management to resource allocation, remain suboptimal, directly impacting profitability and competitiveness in increasingly dynamic markets.
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Every year, thousands of engineering master’s students must complete a thesis, yet finding meaningful real-world research topics is often fragmented and inefficient. At the same time, companies face complex technical challenges in areas such as energy transition, infrastructure, and sustainability but lack accessible research capacity to explore them. Collaboration between universities and industry is largely informal and dependent on personal networks. As a result, valuable research potential remains underutilized while companies miss opportunities to explore innovative solutions and connect with future engineering talent.
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