What Some Students Built With Reka Ai In Four Weeks

What some students built with Reka AI in four weeks

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Jul 8, 2026

What some students built with Reka AI in four weeks

What some students built with Reka AI in four weeks

SummerBuild 2026 is DevHub@iLab’s flagship guided hackathon for students at the Nanyang Technological University, Singapore. Students are given four weeks to design, build, and pitch a portfolio-ready software project. Unlike a 24- or 48-hour sprint, teams had time to learn, receive mentorship, attend workshops, and iterate before a final showcase. This year, Reka joined as sole sponsor, offering a prize for the best use of our API for their project. 25 teams made up of close to 100 students, submitted projects spanning healthcare, sustainability, accessibility, productivity, and everyday life. “SummerBuild gives NTU students the space to experiment with new technologies and turn early ideas into working prototypes. With Reka’s support, our goals this year were to encourage thoughtful AI integration while helping teams go beyond simply building fast — by identifying real problems, designing around users, and pitching solutions with meaningful impact. What stood out was how teams integrated AI to build practical, user-focused products across areas like healthcare, scam prevention, sustainability, accessibility, and everyday productivity.” says Zong Han, Lead Organiser of SummerBuild 2026.

We spoke with the four winning teams to learn more about the innovative solutions that they have developed. Pilly — Overall Champion & Best Use of Reka AI Team: Sunsetters | Prize: Overall Champion + Best Use of Reka AI Award ceremony photo - Team Sunsetters with Simon Tan, Vice President of Sales and Partnerships, Asia Pacific, Reka Pilly was built by five Year 2 NTU Computing students, two of whom had worked inside hospital pharmacies before the hackathon. One had done a part-time stint as a pharmacy assistant at Tan Tock Seng Hospital; another had interned as a nurse at Raffles Hospital Surgery Centre. When the team sat down to brainstorm, they weren’t guessing at problems. They’d seen them firsthand. “Growing up, we’d always wondered why pharmacy queues took so long. After getting behind the counter ourselves, it made a lot more sense. Pharmacists are juggling multiple verification layers on every single order, and that kind of sustained concentration across a full shift is exhausting. Exhaustion is exactly when miscounts and wrong medications slip through.”

Pilly addresses the problem from both sides. For pharmacists, it acts as an AI verification layer: scanning medication labels, counting pills on blister packs and strips, and flagging mismatches before they reach the patient. For patients, it offers real-time queue tracking, delay notifications, multilingual medication instructions (English, Chinese, Malay, and Tamil), and a chatbot that handles the routine questions that would otherwise tie up the pharmacy phone line. How Reka fits in Reka Flash powers two core features: the Ask Pilly chatbot and the medication label scanning in the Scan Medication feature. When a patient photographs their medication and asks a question, “Can I take this with food?”, the image and query go to the Reka Chat API in a single call. Reka reads the label, identifies the medication, and returns a structured answer in the patient’s chosen language. What would normally be a phone call interrupting a pharmacist mid-task resolves in seconds, entirely on the patient’s side. The team chose Reka partly for its enterprise deployment model. In healthcare, where patient medication data is among the most sensitive data there is, a model that supports on-premise deployment means sensitive data stays within approved boundaries, giving the team confidence that Pilly could meet the compliance standards a real hospital would demand. The multimodal capability was equally important. “What really stood out was how naturally it handled different input types, text, images, and even video, all through one API,” the team noted. “For a hackathon where we needed something reliable out of the box, that was a huge time saver.”

Not everything was smooth. Blister pack counting proved harder than expected. The reflective silver foil washed out the edges of each pocket, making a filled blister and an empty one look identical. The team eventually moved pill counting to GPT-4.1 for that specific task, and used a split architecture for translation: Reka for text extraction, GPT-4.1 for Malay and Tamil. “The limitations we hit were very specific edge cases rather than fundamental issues with the model,” the team said. “Overall, the good surprises outweighed the bad.”

Pilly Demo What’s next The team’s first target is a hospital pharmacy like Tan Tock Seng, one of Singapore’s largest and pioneering multidisciplinary hospitals, where they saw the queue, fatigue, and verification problems firsthand. From there, they’re looking at public healthcare bodies like MOH as the most practical path to reaching Singapore’s polyclinic network at scale. The feature they most want to build next: a dispensing robot. “Picture an arm that picks, counts, and packages the medication, then verifies it against the prescription before release. Pairing our software’s intelligence with a physical robot would take us from assisting the pharmacist to genuinely automating the full loop, making it safer, faster, and available around the clock.” — Sunsetters, Team Pilly

AuraSight — Best Smart Cities Solution Team: MeowMeow | Prize: Best Smart Cities Solution Award ceremony photo - Team AuraSight with Simon Tan, Vice President of Sales and Partnerships, Asia Pacific, Reka AuraSight was built by four Data Science and AI freshmen at NTU who found each other through faculty orientation. Their starting point was personal: one team member has an elderly relative who recently began showing symptoms of cataracts and shared the difficulties it brought to daily life. The team looked at what tools existed to help visually impaired people navigate crowded urban spaces, and found the options lacking. The result is a mobile app designed to be worn around the neck, camera pointing forward. Users enter a destination via text or push-to-talk, then receive real-time verbal directions and hazard warnings as they move. Every aspect of the interface was built around accessibility: double-tap to open settings, left- or right-side taps to adjust font size, colour theme, and speech rate, with all on-screen...