The goal of this project is to apply AI and machine learning to selected apps within Appy.yo’s Innovation Lab. Students will explore how to integrate intelligent features—such as personalized recommendations, automated workflows, or smart data analysis—into our apps.

👉 AI/ML could be applied to Cookful (predicting recipes from fridge items), Physio App (generating safe routines), Rolodex (intelligent contact matching), eGift (personalized gift suggestions), Poste (content filtering), FlexyGig (matching jobs to workers), or WeVibe (sentiment tracking).

By the end of this project, students will have produced:

Core Deliverables (required):

• Exploration Report – focused on one or two selected Innovation Lab apps (e.g., Cookful or Rolodex), documenting potential AI/ML use cases and why they were chosen.
• Prototype Model – at least one trained AI/ML model (e.g., recipe prediction for Cookful, contact matching for Rolodex) that demonstrates the feasibility of the chosen feature.
• Evaluation Report – an assessment of model performance, challenges encountered, and recommendations for improvement.

Optional Deliverables (flexible/for exploration):

• Data Preparation Artifacts – datasets cleaned, simulated, or generated during the project.
• Alternative Models Tested – comparison of different approaches or algorithms and notes on their relative performance.
• Integration Concept – mockups, flow diagrams, or a proof-of-concept showing how the AI/ML feature could be embedded into the app experience.

Expected Outcome:

Students will develop a focused, working prototype supported by clear research and evaluation, while also having the flexibility to explore additional models, datasets, or integration concepts if time and interest allow. This balance ensures both consistency across teams and room for creativity.