Never Weight

Inspiration

Northwestern gyms get crowded quickly, and students often waste time walking around trying to find an open machine. We wanted to create a tool that makes the gym experience more efficient, predictable, and motivating. Never Weight was built to give students real-time visibility into machine availability while also helping them track their workouts and progress.

Project Title and Description

Title

Never Weight

Description

Never Weight is an app that tracks foot traffic at Northwestern University gyms and helps users document their workouts. Users can log the machines they use—along with weights, reps, and settings—to build a personal workout history. A streak feature encourages consistent gym attendance, and weekly summaries highlight muscles trained, visit frequency, workout patterns, and AI-generated workout suggestions tailored to user goals. With Never Weight, you never wait.

What It Does

Never Weight provides real-time machine availability using AI, logs workouts, tracks streaks, and generates weekly summaries with personalized workout suggestions. It also offers gym staff insights into machine usage, cleaning needs, and equipment maintenance.

How We Built It

Integrated the Gemini API for AI-powered workout suggestions
Designed a clean, minimal interface to avoid overwhelming users

Challenges We Ran Into

Making the interface intuitive for users of different ages and comfort levels with technology
Balancing convenience with simplicity while avoiding a congested UI
Determining which features were essential for the MVP and which should be saved for future versions
Managing the scope of the project given how many directions it could expand

Accomplishments That We're Proud Of

Creating a clean, intuitive interface that works for a wide range of users
Designing a system that benefits both gym-goers and gym staff
Establishing a foundation that can scale into a more comprehensive fitness platform

What We Learned

How to scope and prioritize features in a project with many potential directions
How to design for accessibility and user convenience
How to consider both user experience and gym operational needs

Features

Real-time foot-traffic tracking using existing cameras and AI
Privacy-first design with encrypted processing and no stored identifiable data
Operational insights for staff, including machine usage frequency, cleaning priorities, purchasing guidance, and automatic detection of broken or inactive machines

What's Next for Never Weight

We plan to expand the app to include AI-generated meal suggestions based on dining hall menus (via the Dine on Campus website) and campus restaurants such as Buen Día and Shake Smart. Users will be able to receive meal recommendations aligned with their macro goals, favorite dining locations for personalized suggestions, and combine workout and nutrition insights for a more holistic fitness experience.