Build a Scalable Inventory System for a Small-Batch Dessert Startup Preparing for E-Commerce

Gina’s Gelato is a young, small but growing, owner-operated gelateria and dessert shop (brick & mortar, single location) now entering its fourth year of business. Our current inventory tracking relies on handwritten tallies, leading to frequent errors, difficulty tracking sales trends, and the inability to reliably launch an e-commerce store. We are seeking students who are interested in building a practical, easy-to-use, real-time inventory management system. This system will lay the critical groundwork for a future e-commerce site, integrating directly with our existing Square POS (sandbox API provided for secure testing). If your course allows, educators may optionally expand the scope to include the e-commerce build itself —using Square’s sandbox tools to create a basic but functional online storefront. This would allow students to see their work come to life in a real-world setting, supporting both the inventory system and its live integration into a customer-facing sales channel. The framework of this project is two-fold: Primary Focus: Building a robust inventory management system that will allow us to keep track of inventory trends over time (day/week/month/year, YOY, etc.) of various product categories and variations (e.g. Category: Gelato, variations: chocolate, coffee, etc.; Category: Cookies, variations: chocolate chip, hazelnut biscotti, mocha, etc.) Secondary Focus: Ensuring the system is built with the perspective of integrating with a future e-commerce platform. Students may provide a basic working prototype or proof-of-concept demonstrating inventory synchronization capability via the Square POS Sandbox environment. Detailed documentation or instructions for future integration should be included. Business Context & Impact: This project directly helps our small but growing business by solving key operational challenges: Real-time Inventory Tracking : Eliminates manual errors; allows precise analysis of historical data (daily, weekly, monthly, yearly, year-over-year comparisons) to forecast ingredient ordering, manage costs, and minimize waste. Foundation for E-commerce Growth :Without a real-time integrated system, launching an online store is impractical. Inventory moves rapidly during busy periods, making manual updating impossible without negatively affecting customer experience. The practical solutions students deliver will directly support our ability to grow revenue; expand our market reach; support more job creation; and improve customer experience both in-store and online. Student Mentorship & Resources: We are dedicated to supporting student success: Direct mentorship provided by Gina, the business owner and operator, offering insights and guidance throughout the project. Regular feedback and availability for consultation as needed. Access provided to Square’s Sandbox API environment for secure development and testing. Provision of any necessary hardware/software resources, such as barcode scanners or database hosting (within reasonable budget constraints). Real-world sales and inventory data to help students test, validate, and refine their solutions. Why This Project is Unique: This opportunity offers students meaningful, hands-on experience developing a practical, immediately impactful solution for a growing small business. Rather than a theoretical exercise, students will directly contribute to a tangible, real-world outcome that will help shape the next stage of growth for Gina’s Gelato. They will also build valuable experience in developing scalable, user-focused solutions aligned with specific operational challenges and small-business realities. Next Steps for Interested Educators & Students: Please review the clarified scope above carefully. If this aligns with your course objectives and student capabilities, we’d be delighted to discuss further. We welcome any questions or suggestions to ensure mutual clarity and successful outcomes. Thank you for your consideration—we're excited about the possibility of collaborating!

Preserving Craft with Code: An AI Project to Protect the Craft of Heritage Dessert Making in Modern Times

Help a small-batch dessert company reduce food waste, preserve a centuries-old culinary craft, and train the next generation using applied AI! This project supports UN SDG 12 (Responsible Consumption & Production) and SDG 4 (Quality Education) by reducing food waste, preserving culinary heritage, and training the next generation in sustainable, local, and all-natural culinary traditions using AI. Gina’s Gelato is a small-batch dessert company in Nelson, BC, producing from-scratch gelato, sorbetto, and other desserts using all-natural ingredients and traditional food-processing methods. We avoid synthetic stabilizers, industrial emulsifiers, artificial colours and flavours, and lab-engineered additives, focusing instead on whole ingredients and small-batch techniques like blending, baking, steaming, cooking, and churning. We are building an internal AI-powered tool to support real-time recipe development, ingredient substitutions, and product troubleshooting while adhering to our all-natural, from-scratch ethos ("slow food" philosophy). The tool will be trained using our in-house knowledge base, made up of our formulation PDFs, recipes, and handwritten or scanned notes. It must be expandable over time as more documents and data are added. The goal is to create a system that allows our kitchen team—and future culinary students or interns—to create and/or adapt recipes, ask ingredient-related formulation questions, troubleshoot product issues, and understand ingredient impacts on texture, freezing point, stability, etc. without relying solely on the owner/operator (Gina), who currently handles all recipe creation, training, and technical oversight as well as other aspects of running the business. This tool will reduce food waste, improve kitchen efficiency, and serve as a reference and educational aid within our kitchen. There are very few formal educational programs dedicated to from-scratch gelato or dessert formulation—especially those rooted in all-natural ingredients and traditional methods. This centuries-old craft is increasingly being replaced by lab-engineered bases and industrial shortcuts, even in artisan-labelled products. This project helps protect that knowledge in a small but meaningful way by building a tool that allows our team—and future culinary students or interns working with us—to learn directly from our recipes, scientific reasoning, and process logic. It supports the preservation of time-honoured techniques by helping users bypass modern artificiality and work confidently with whole ingredients, including local and/or organic when possible, while also streamlining the recipe development process for our core staff. While the tool is designed to support recipe generation and learning, all proprietary recipes, PDFs, and internal documents used to train the system must remain hidden and inaccessible to users. These materials are to be used only for training the AI to provide accurate, science-informed outputs—without being exposed or downloadable. Student collaborators will: Assess feasible technical approaches suitable for a non-technical business owner Design a user-friendly interface for querying gelato/sorbetto/frozen dessert-specific questions Recommend a scalable, low-maintenance, and cost-stable system Ensure the system allows uploads of new recipe scans, PDFs, or photos to expand the knowledge base over time Ensure users can generate complete, functionally correct recipes through queries, but cannot view, download, or access the underlying training materials (e.g., PDFs, scanned notes, proprietary recipes). These source documents must remain hidden and protected, used only to inform the AI’s responses—not exposed directly to the user. Ensure adherence to provided constraints (including our all-natural ingredient standards, from-scratch methods, slow food philosophy, and reference materials such as our PDFs and handwritten notes) Minimize AI hallucinations, as inaccurate outputs affect real-world business operations, job performance, confidence, and education. Deliverables will include a research-backed platform recommendation, a working prototype (if feasible), and documentation for setup, usage, and future expansion.