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Reimagining the In-Store Experience with Technology United Kingdom

allhackathonsHosted on All Hackathons

Fetched about 1 month ago

Wednesday, December 3, 2025

Artificial IntelligenceData ScienceHealthtechSocial Impact
Student only
This hackathons is only open to students. Double check the event page for more information as this may mean only those from a particular university/country are eligible.

Event Type

online

As part of UST’s ongoing mission to drive innovation in the food service and retail space, the QSR Hackathon 2025 invites innovators, students, and professionals to design AI-powered solutions that transform how Quick Service Restaurants, making them faster, smarter, and more human. The quick service restaurant (QSR) industry is at a turning point. Customers expect speed, personalization, and convenience, yet many QSRs are still built on systems that prioritize throughput over experience. The result: long queues, inaccurate orders, and disconnected digital touchpoints that leave customers frustrated. Even though QSRs generate huge volumes of data from point-of-sale systems, delivery platforms, and loyalty apps, this data is rarely used in real time to improve decisions. Restaurants often can’t predict sudden changes in demand, optimize staff scheduling, or personalize menus dynamically. This hackathon challenges participants to rethink what “fast service” really means in the age of AI, to design intelligent, data-driven solutions that can predict demand, adapt operations instantly, and create seamless, personalized customer experiences across dine-in, drive-thru, and delivery environments. Artificial Intelligence is redefining how quick service restaurants serve, engage, and operate. The goal of this hackathon is to uncover what the next leap could look like, how technology can make the QSR experience faster, smarter, and more intuitive without losing its human touch. AI opens up countless possibilities for innovation across the QSR value chain: -Customer Experience: Use generative or conversational AI to personalize menus, predict customer intent, or recommend meal combos based on time, behavior, or context. -Operational Intelligence: Build systems that optimize order flow, kitchen workloads, and staff scheduling dynamically as demand fluctuates. -Smart Logistics: Explore predictive delivery management, from real-time traffic-based routing to kitchen prep synchronization, to minimize wait times and errors. -Sustainability and Efficiency: Apply data analytics to reduce food waste, energy usage, and idle capacity, linking operational excellence with environmental goals. -Immersive Interactions: Imagine next-gen interfaces, voice-enabled kiosks, AR-enhanced ordering, or vision-based service tracking, that elevate both convenience and delight. Participants are encouraged to think beyond traditional restaurant models, to design AI-driven, scalable, and ethically responsible solutions that can work across multiple QSR formats and geographies. The best ideas will combine technical ingenuity with empathy for the end-user, bridging data, design, and business impact.

Judge Accessibility

Organizer email available25/25
Student-run event15/15
Actively looking for judges25/25
Small event (120 participants)10/10
No corporate sponsors10/10
New or emerging organizer10/10
Public registration available5/5
Online format (judge from anywhere)10/10

Top signals

Organizer email available
Student-run event
Actively looking for judges

Organizers

Alex Johnson

alex@example.org

Jamie Rivera

jamie@example.org

Sam Chen

sam@example.org

Estimated Audience

Mostly Students
ExperienceStudent
OccupationStudents
Beginner Friendly
Women in Tech

Technical Focus

AI95%
Web80%
Mobile25%

Industries

Healthcare
Education
Climate

Technologies

Python
React
OpenAI

Why this estimate

  • • Hosted by a university
  • • Open to students
  • • MLH member event

Estimate inferred from event metadata, not actual attendee data.

Quality Score

Quality Score

72/100
High confidence
Organiser16/20
Event Maturity14/20
Sponsors18/25
Participants12/20
Operations12/15

Why this score

Strong organiser track record
Returning event
Well-sponsored

Missing data

Prize details
Code of conduct