Cooking | Generative AI | Product
2 Weeks
Product Manager
Chef'd is a recipe generation app designed to provide users with personalized recipe recommendations based on the ingredients they have available in their pantry. The app leverages the power of OpenAI API, Firebase, and Next.js to deliver a seamless and efficient user experience. This case study highlights the key features, challenges, and outcomes of developing and launching Chef'd.
The main objective of Chef'd is to simplify the cooking experience for users by offering them customized recipe suggestions that utilize the ingredients they already have at home. The app aims to save users time and effort in meal planning while promoting resourcefulness and reducing food waste. We are targeting university students who stay away from family and are health conscious.
Key Features
Ingredient Selection: Chef'd enables users to input the ingredients available in their pantry.
Recipe Recommendations: The app utilizes OpenAI API to recommend recipes that best fit the ingredients at home with minimal extra ingredients. Using data on user preferences, dietary restrictions, and cuisines, Chef'd generates personalized recipe recommendations tailored to each user's unique taste and ingredient availability.
Dynamic Recipe Filtering: Chef'd allows users to filter recipe suggestions based on specific criteria such as dietary preferences, cooking time, cuisine, and more. This feature ensures that users can find recipes that suit their preferences and requirements.
Challenges and Solutions
Recipe Relevancy and Diversity: Ensuring recipe suggestions were relevant and diverse was crucial for a satisfying user experience. The machine learning algorithms were continuously refined to improve the quality of recommendations, considering factors such as popularity, user feedback, and ingredient compatibility.
Scalability and Performance: As the user base grows, it is essential to maintain app performance and responsiveness. Next.js was utilized to optimize the app's speed, server-side rendering, and caching, ensuring a smooth experience even during peak usage.
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