Drafting product specifications

​

Executive Summary

​

Target User Analysis

• Goals: Quick meal ideas, use existing ingredients, healthy eating
• Pain Points: Lack of cooking inspiration, food waste, time constraints

​

Feature Specifications

1. AI Ingredient Recognition
   • User Story: “As a user, I want to snap a photo of my fridge contents and get recipe suggestions”
   • Requirements: Computer vision API, ingredient database, accuracy >90%
2. Personalized Recipe Engine
   • User Story: “As a user, I want recipes that match my dietary preferences and skill level”
   • Requirements: User preference profiling, recipe difficulty scoring, dietary filters
3. Smart Shopping Lists
   • User Story: “As a user, I want to generate shopping lists for missing ingredients”
   • Requirements: Recipe parsing, inventory tracking, grocery store integration

​

Technical Requirements

• Platform: iOS/Android native apps
• Backend: Cloud-based ML models, recipe database API
• Performance: <3 second photo processing, offline recipe viewing

​

Success Metrics

• User Retention: 80% after 30 days
• Engagement: 3+ recipes generated per user weekly
• Satisfaction: 4.5+ app store rating
• Conversion: 25% of users upgrade to premium within 60 days

​

Implementation Timeline

• Phase 1 (Months 1-2): Core photo recognition, basic recipe database
• Phase 2 (Months 3-4): Personalization engine, dietary filters
• Phase 3 (Months 5-6): Shopping list integration, premium features

​

Risk Assessment

• Technical: AI accuracy may vary with photo quality
  • Mitigation: Extensive training data, user feedback loop
• Market: Competitive recipe app landscape
  • Mitigation: Focus on unique photo-to-recipe workflow