Pod Orion
SkillMatch
Product Design - 1 membersCelebrating the achievements of our top participants and alumni teams, showcasing the innovation and excellence demonstrated during our hackathon events.
SkillMatch
Product Design - 1 membersCHECKPOINT
Health Tech / Business Analysis - 4 membersCareerGPS
Data Science - 3 membersThe winning team of the Q3 10Alytics Student's Hackathon 2026, permanently enshrined on the wall.

Many early-career workers can feel AI changing their job, but they cannot tell what to do about it. They know what they have done, yet not how it turns into skills a new role would want. SkillMatch comes in at this point. A user describes their experience in plain words, SkillMatch suggests skills from it and shows its working, so the user can confirm, edit or remove each one and then shows careers that could suit the user, explains why, names the skill gaps and builds a short plan they can save. SkillMatch's AI never decides for the user. It guesses, explains and waits. The impact is clarity and confidence for each user, as a user leaves with a next role in mind and a first small step to take.
data & strategy
Build the Future. Earn the Crown.
Augist Cohort 2026 - Product Design - Product Design
Hi, I’m Emmanuel, a product designer and computer science student who surely gets a little too excited about turning complex and even unique experiences into clear and simple designs. I’m on the Product Design track at 10Alytics (cohort C26-05), where I’ve been learning to design with real people in mind, not just aesthetic screens. I love human-centred design, research-driven decisions and anything that helps someone feel less lost. For the hackathon, I went solo and designed SkillMatch, an app that helps early-career workers see which skills they already have and which roles they could grow into as AI changes work. I ran a survey, created a persona called Daniel, built a design system, designed the screens, wired up a prototype, and wrote the pitch, all in a very short, very busy stretch of time. Spoiler...it won!
Winner ReflectionWinning still feels a bit unreal. I came across some really impressive projects on showcase night. The biggest thing I learned is that people trust AI more when it shows its reasoning and lets them correct it, which is why SkillMatch tells you which skills are yours and which are guesses. My advice to future participants: pick one real person to design for (mine was Daniel), be honest about what you don’t know yet, and DON'T skip the research, even when the countdown pressures you. This win is proof that I can design for real problems even as a solo designer, and it gives SkillMatch a shot at life beyond the hackathon.

August Cohort 2026 - Health Tech / Business Analysis
Checkpoint is a decision-rights framework and working prototype for Lakeside Health Network, formed when Lakeside General and Riverside Specialist merged. The network wants AI to predict which patients are likely to be readmitted within 30 days of discharge, so nurses can prioritise follow-up. The real risk isn't the algorithm, it's that two hospitals run different systems, records can be duplicated across sites, and no one has defined who owns a decision once AI is in the loop. Checkpoint answers that with one rule: AI narrows the decision, a human owns it. The solution redesigns the discharge workflow around four mandatory human checkpoints; identity matching, low-confidence review, tier approval, and monthly governance each with a clear accountable role. A working prototype demonstrates all four checkpoints live, across three role views: follow-up nurse, Health Records steward, and governance committee. Every AI action is logged, explained in plain language, and reversible.

September Cohort 2026 - Data Science
CareerGPS is a workforce intelligence tool built for StrataWork Global, where AI has already automated 65% of entry-level analytics tasks, leaving junior and mid-level staff facing displacement with no clear next step. The app does two things: it estimates how exposed a given job is to automation using a transparently-tested machine learning model, and it recommends realistic career transition paths based on the skills a person already has, prioritizing safer pivots for at-risk roles and growth paths for stable ones. What makes CareerGPS different is honesty. We tested our data rigorously before trusting it, found the provided labels carried weak statistical signal, and built our model, our reporting, and even our UI around disclosing that limitation clearly rather than hiding it. We paired our own model with an independent, real-world research benchmark, so users always see two honest perspectives, not one overconfident number.
Pod leaderSeptember Cohort 2026 - Data Science with AI and Machine Learning
September Cohort 2026 - Data Science with AI and Machine Learning

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August Cohort 2026 - Health Tech / Business Analysis
MemberAugust Cohort 2026 - Health Tech / Business Analysis
September 2026 Cohort - Data Science with AI and Machine Learning
