FoodNeural is a free AI-powered food safety scanner and pantry management platform. It uses neural vision AI to scan food items and instantly tells you whether they are safe to eat, fresh, correctly labelled, and nutritionally honest. It tracks your pantry inventory, grocery spending, diet macros, and generates personalised meal plans.

Is FoodNeural free to use?

Yes, FoodNeural is free to use. New users get 10 free AI scan credits. Additional credits can be purchased or earned through referrals. Basic pantry tracking, diet logging, and spend tracking are completely free with no credit cost.

How does FoodNeural detect if food is safe to eat?

FoodNeural uses Google Gemini multimodal AI to visually analyse food images. It checks for spoilage indicators, cross-references ingredient lists against FSSAI regulations, evaluates expiry dates, and assigns a health safety score. It can detect misleading health claims on packaged food labels in seconds.

Can FoodNeural scan nutrition labels and ingredient lists?

Yes. FoodNeural scans printed nutrition labels and ingredient lists on packaged food. It identifies hidden sugars, sodium, trans fats, and artificial additives. It also flags misleading marketing claims like 'zero sugar' or 'heart healthy' that may be deceptive under FSSAI guidelines.

Does FoodNeural work for Indian food and local brands?

Yes. FoodNeural is specifically trained to recognise Indian pantry items, local packaged food brands, fresh vegetables, spices, dal, rice, dairy products, and regional cuisine. It provides FSSAI-aligned safety ratings alongside global nutrition standards.

How does FoodNeural reduce food waste?

FoodNeural tracks your pantry inventory in real time, sends expiry alerts before food goes bad, predicts which items will run out first using AI consumption velocity, and suggests meal plans using items you already have. Users typically prevent 15–20 kg of food waste per month.

Is my food and health data private on FoodNeural?

Yes. FoodNeural operates on a privacy-first architecture. You can use Bring Your Own Key (BYOK) mode to ensure your AI scans are processed using your own API key and data never leaves your control. No personal health data is sold to third parties.

How accurate is FoodNeural's calorie and nutrient tracking?

FoodNeural achieves ±12-15% accuracy in image-only mode and ±5-8% with GrocerTech sensor calibration, compared to ±25-40% industry average for competing calorie trackers. It uses a 7-step Nutrient Estimation Protocol: (1) Container detection and weight estimation using reference objects, (2) Cooking method identification from visual evidence, (3) Ingredient decomposition into constituent components, (4) Per-100g reference lookup from USDA FoodData Central and IFCT 2017, (5) Cooking-method adjustments for oil absorption and vitamin degradation, (6) Sensor calibration for vitamin C/A via spectral analysis, and (7) Confidence scoring with auditable calculation notes. When a nutrition label is visible, OCR values take absolute priority over estimation.

What nutrients does FoodNeural track?

FoodNeural tracks 18 nutrients per scan: Calories (with ±10% range), Protein, Total Fat, Saturated Fat, Trans Fat, Carbohydrates, Sugar, Fiber, Sodium, Cholesterol, Iron, Calcium, Potassium, Vitamin A (RAE), Vitamin C, Vitamin D, Vitamin B12, and Folate. All values are numeric and calculated from evidence-based reference databases — not guessed. For complex cooked dishes, FoodNeural decomposes ingredients individually and applies cooking-method adjustments (oil absorption, vitamin heat-degradation, bioavailability enhancements).

How is FoodNeural different from other calorie tracking apps?

FoodNeural is fundamentally different from both manual-entry calorie counters and basic photo estimator apps. Key differences: (1) Ingredient decomposition — FoodNeural breaks complex dishes into constituent ingredients with individual weights and reference kcal/100g values. Typical apps report a single estimated number. (2) Cooking-method science — FoodNeural adjusts for oil absorption (+40% calories for deep-fried), vitamin C heat-degradation (-50% for deep-fried), and bioavailability enhancements. (3) Container-based weight — FoodNeural analyses the plate or bowl dimensions and uses reference objects for scale rather than guessing portion size. (4) Hardware sensor calibration — With GrocerTech's spectral, thermal, and gas-phase sensors, FoodNeural can achieve ±5% accuracy. (5) Full micronutrient profile — 18 nutrients including vitamins and minerals, not just macros.

Can FoodNeural track calories for Indian food like chilly paneer, biryani, or thali?

Yes. FoodNeural excels at Indian cuisine calorie tracking because it uses ingredient decomposition rather than flat estimates. For a thali, it identifies each katori, estimates volume (~120ml each), decomposes each dish into raw ingredients, applies cooking adjustments (e.g. ghee-based tarka, deep-fried pakoras), and references the Indian Food Composition Table (IFCT 2017) for region-specific nutritional data. A biryani is broken into basmati rice, marinated chicken, fried onions, whole spices, saffron-infused oil, and ghee — each component calculated individually.

What is GrocerTech sensor suite and how does it improve calorie accuracy?

The GrocerTech Sensor Suite is proprietary hardware built into FoodNeural's smart pantry cabinet. It includes an 18-channel spectral sensor (AS7341) for detecting chlorophyll (vitamin C/K), carotenoids (vitamin A), and water content (fiber density); a contactless infrared thermometer (MLX90614) for cooking state verification; VOC and CO₂ sensors (SGP30, SCD41) for ripeness and fermentation detection; and a camera module. When sensor data is available, FoodNeural calibrates AI estimates with measured physical data — for example, adjusting vitamin C content based on actual NDVI readings rather than database averages.

FoodNeural — AI Calorie & Nutrient Tracker | Lab-Grade Food Scanner & Diet Intelligence

FoodNeural is the world's most advanced AI calorie and nutrient tracker. Scan any food — home-cooked, restaurant, or packaged — and get lab-grade nutrition analysis with 18 nutrients, ingredient decomposition, cooking-method adjustments, and optional hardware sensor calibration. Free AI food scanner for realistic diet tracking. Works across India and globally.

Most Accurate AI Calorie Tracker — How FoodNeural Works

FoodNeural's 7-Step Nutrient Estimation Protocol: Step 1: Container Detection — AI identifies the plate, bowl, katori, or takeaway container and analyses its dimensions using reference objects. Step 2: Weight Estimation — calculates food weight from container volume × fill level × food density. Step 3: Cooking Method Analysis — detects deep fried, pan fried, steamed, tandoor, grilled, etc. from visual evidence (oil sheen, batter crust, char marks). Step 4: Ingredient Decomposition — breaks complex dishes into constituent raw ingredients with individual weights. Step 5: Reference Database Lookup — calculates nutrients from USDA FoodData Central and IFCT 2017 per-100g values. Step 6: Cooking Adjustments — applies oil absorption (+40% calories for deep-fried), vitamin degradation (-50% vitamin C for frying), and bioavailability enhancements. Step 7: Sensor Calibration (when available) — adjusts vitamin C/A from spectral NDVI, sugar from VOC ripeness, and cooking state from infrared thermometer.

18 Nutrients Tracked Per Scan

Calories (with ±10% confidence range), Protein, Total Fat, Saturated Fat, Trans Fat, Carbohydrates, Sugar, Fiber, Sodium, Cholesterol, Iron, Calcium, Potassium, Vitamin A, Vitamin C, Vitamin D, Vitamin B12, and Folate. All values are numeric and evidence-based — not estimated from memory.

What does FoodNeural do?

FoodNeural is an AI-powered platform that lets you photograph any food item — packaged or fresh — and instantly receive a food safety score, ingredient analysis, nutrition breakdown, and expiry risk assessment. It detects misleading health claims, identifies allergens, tracks your pantry inventory, and generates AI meal plans based on what you already have.

FoodNeural vs Traditional Calorie Trackers

Unlike manual-entry calorie counters or basic photo estimators, FoodNeural decomposes ingredients, adjusts for cooking methods, estimates weight from container analysis, and optionally calibrates with hardware sensors. Result: ±5-8% accuracy with sensors vs ±25-40% industry average. The only calorie tracker that shows you exactly how every number was calculated.

Is FoodNeural free?

Yes. FoodNeural is free to use. New users receive 10 free AI scan credits. Basic pantry tracking, diet logging, and spend analytics are completely free.

How accurate is FoodNeural's food safety detection?

FoodNeural uses Google Gemini multimodal AI, the same technology used by enterprise food safety labs. It cross-references FSSAI regulations, WHO nutrition guidelines, and real-world food safety databases to deliver honest, unbiased food safety assessments.