Please check the pdf for full brief and only bid if budget 25,000 is acceptable. I’m building an iOS & Android mobile app that allows users to scan the ingredient list and nutrition table on packaged food products and instantly see whether the product is healthy, okay, or unhealthy based on predefined rules and user dietary goals. This is a rule-based MVP, not a custom AI/ML research project. Core Features Required:- 1. User Authentication Email + password signup & login Use Firebase Authentication 2. Camera Scanner (Main Screen) Camera opens immediately after login Users scan ingredient list and nutrition table Flashlight (torch) ON/OFF toggle Auto-focus support Works well in low-light environments 3. OCR (Text Extraction) Extract text from scanned images Preferably using Google ML Kit OCR Clean and structure the extracted text 4. Health Evaluation Logic Apply predefined, rule-based logic (rules will be provided) Output one of: Green (Healthy) Yellow (Okay occasionally) Red (Unhealthy) 5. Result Screen Show colour-based verdict clearly Explain why (e.g., added sugar, additives, refined flour) Highlight problematic ingredients Suggest healthier alternatives for Yellow & Red products Verdict should adapt based on user-selected dietary goal (e.g., high protein, sugar-free, weight loss, energy) 6. Dietary Goal Selection User selects one primary goal during onboarding Verdict logic adapts to this goal 7. Scan History (Optional if time permits) Store past scans per user Tech Stack Preference:- Frontend: Flutter Authentication & database: Firebase OCR: Google ML Kit Platform: iOS & Android