App Overview
Floora is a nutrition and meal-planning application designed to support users who care about PCOS-friendly eating patterns. The app helps users log foods by portion size, estimate calories and nutrients, and understand how a food may affect satiety, blood-glucose stability, antioxidant intake, and anti-inflammatory dietary quality.
- Food portion input and nutrition estimation
- Calories, protein, carbohydrate, fat, fiber, and sugar display
- PCOS-oriented food grades: A, B, C, and D
- Insights explaining why a food is supportive, balanced, or likely to need adjustment
- Small, practical food-upgrade suggestions
- Recipe library and meal-plan support
Floora provides educational nutrition information and lifestyle support insights. It does not diagnose PCOS, treat PCOS, guarantee health outcomes, or replace medical advice from qualified clinicians or registered dietitians.
Regulatory and Safety Positioning
Floora is designed as a general wellness and nutrition education product. The grading and insight features help users compare food choices and understand nutrition trade-offs. They do not determine whether a food is medically allowed or prohibited.
- No diagnosis: Floora does not diagnose PCOS, insulin resistance, diabetes, eating disorders, fertility conditions, or any medical condition.
- No treatment claim: Floora does not claim that a food, meal plan, or recommendation can cure, treat, reverse, or prevent PCOS.
- No medication guidance: Floora does not advise users to start, stop, or modify medication or clinical treatment.
- No absolute food prohibition: Food grades are comparative educational signals, not moral judgments or medical restrictions.
- Escalation to professionals: Users with medical conditions, pregnancy, diabetes, eating disorder history, severe symptoms, or individualized dietary requirements should consult qualified healthcare providers.
Food Grade Design Principle
Floora uses an A/B/C/D grade to translate a multi-factor nutrition assessment into a simple user-facing signal. The letter grade makes food logging easier to understand while keeping the underlying explanation visible through calories, nutrient values, dimension labels, and written insight.
The grade is not a universal definition of whether a food is healthy. It is a Floora-specific educational summary focused on PCOS-oriented meal quality across four practical dimensions: high protein support, insulin safety, antioxidant-rich food quality, and anti-inflammatory dietary support.
Nutritional Data Sources
Food nutrition values may be derived from recognized nutrition databases, food labels, structured recipe data, or user-provided and AI-estimated food recognition results. Preferred data references include:
- USDA FoodData Central
- Dietary Guidelines for Americans
- World Health Organization healthy diet guidance
- Harvard T.H. Chan School of Public Health Nutrition Source
- International evidence-based PCOS guideline resources
Nutrition data may include calories, protein, carbohydrate, fat, fiber, sugar, and selected micronutrients when available. When exact brand or recipe-level values are unavailable, Floora presents values as estimates rather than exact measurements.
Portion and Calorie Calculation
Floora calculates food nutrition based on portion size. If a food item has nutrition data per 100 g, the app scales values as follows:
Estimated Nutrient Amount = Nutrient per 100 g x User-entered grams / 100
If only macronutrient grams are available, calorie estimates may use standard Atwater energy factors: protein at 4 kcal/g, carbohydrate at 4 kcal/g, and fat at 9 kcal/g.
Total Calories = Protein x 4 + Carbohydrate x 4 + Fat x 9
Photographed meals, mixed dishes, sauces, cooking oil, and hidden ingredients can be difficult to estimate accurately, so image-based or manually entered nutrition results are approximate values.
Food Grade System
Floora first calculates an internal numeric score from 0 to 100. This internal score is then converted into a user-facing food grade.
| Internal Score Range | Food Grade | User-facing Meaning |
|---|---|---|
| 85-100 | A | PCOS-supportive choice |
| 70-84 | B | Mostly balanced choice |
| 55-69 | C | Needs balancing or pairing |
| 0-54 | D | Use with caution; likely needs adjustment |
The grade should be used to compare similar foods, understand meal composition, and identify small improvements. It should not be used to label foods as absolutely good or bad.
Internal Scoring Dimensions
| Dimension | Weight | Positive Signals | Negative Signals |
|---|---|---|---|
| High Protein Support | 25% | Meaningful protein amount, lean protein, legumes, eggs, fish, tofu, Greek yogurt | Very low protein meals, especially with high carbohydrate load |
| Insulin Safety | 35% | Fiber, protein pairing, lower added sugar, whole grains, legumes, vegetables | High sugar, refined carbohydrates, high glycemic load, sugary drinks, low fiber |
| Antioxidant Rich | 20% | Colorful vegetables, leafy greens, berries, tomatoes, peppers, legumes, herbs, spices | Low plant diversity or low micronutrient density |
| Anti-inflammatory Support | 20% | Fish, omega-3 sources, olive oil, nuts, seeds, legumes, vegetables, fermented foods | Fried foods, highly processed foods, sugary foods, processed meats, excess saturated fat signals |
Insight Generation Logic
Floora generates insights from structured nutrition features and scoring signals. Insight text explains whether a food appears supportive, balanced, or problematic; identifies the key nutrition reason; and describes likely nutrition-related effects such as satiety, blood-glucose stability, or anti-inflammatory support.
- High sugar or refined carbohydrate signals may trigger blood-glucose stability context.
- Low protein signals may trigger weaker satiety and reduced glucose-stabilizing support context.
- Low fiber signals may trigger limited support for glucose stability and gut-friendly eating context.
- Low antioxidant signals may suggest colorful plants such as leafy greens, tomatoes, peppers, or berries.
- Low anti-inflammatory signals may suggest fish, olive oil, nuts, seeds, legumes, or vegetables when appropriate.
Insight generation is educational and descriptive. It does not predict an individual user's actual glucose response, hormone response, weight change, fertility outcome, or clinical improvement.
AI Usage Disclosure
Floora may use AI to interpret food images, normalize user-entered food descriptions, estimate food composition, and generate readable nutrition insights. AI output is constrained by structured nutrition data, rule-based scoring dimensions, and safety language that avoids medical diagnosis or treatment claims.
AI-generated outputs may be inaccurate when:
- The image is unclear, cropped, or contains visually similar foods
- Serving size is misestimated
- Cooking oil, sauces, sugar, or hidden ingredients are not visible
- The food is a mixed dish or restaurant item with unknown recipe details
- The database item does not match the exact brand or preparation method
Limitations of the Food Grade
Food grading is a simplification. A single grade cannot fully represent a user's total diet, medical history, cultural food pattern, budget, preferences, medication, activity level, or individual glucose response.
- Serving size matters.
- Context matters.
- Healthy high-fat foods may be nuanced.
- Database completeness varies.
- PCOS needs vary.
- Floora is not a glucose prediction model.
User-facing Disclaimer
Floora's food grade, calorie estimate, nutrition analysis, and PCOS insight are for general wellness education only. They are estimates based on available food data, portion input, and AI or rule-based interpretation. They are not medical advice and should not be used to diagnose, treat, cure, or prevent any disease. Users should consult qualified healthcare professionals for personalized medical or nutrition guidance.