Your data stays with you.

A. Categories of Processed Data

The local database includes the following data categories:

• 1. Profile Settings and Goals: Username, date of birth, body height, gender, profile picture file path, and individually defined daily goals (target calories, target protein, target carbohydrates, target fat, target water, target steps).
• 2. Training and Activity Logs (Workouts): Training plans (routines), exercise templates, historical workout logs (start and end times, notes, exercise sets with rep and weight values, RPE and RIR values, rest times, cardiovascular activities including distance, duration, and calories burned).
• 3. Nutrition and Fluid Logs (Nutrition & Fluids): Consumed food items (timestamp, amount in grams/milliliters, meal type), water and beverage logs (amount, nutrient content, caffeine content).
• 4. Food and Product Catalog (User-Products): Products individually created by the user, including barcode, product name, brand, and macro/micronutrient information per 100g/ml (calories, protein, carbohydrates, fat, sugar, dietary fiber, salt, caffeine, list of ingredients, and additives).
• 5. Supplements: Set up supplements (name, default dose, unit, daily goal, and daily limit) as well as historical supplement log entries with intake timestamp and amount.
• 6. Body Dimensions and Measurements (Measurements): Historical measurement values for body weight and various body circumferences (e.g., chest, waist) including date and unit.
• 7. Heart Rate Data Aggregates: Local hourly aggregations of heart rate (minimum, maximum, and average beats per minute, as well as sample count).
• 8. Sleep Data Analyses: Processed sleep data including sleep phases (deep sleep, REM, light sleep, waking phases), sleep efficiency, resting heart rate, sleep interruptions, sleep regularity, as well as historical raw data imports from system interfaces.
• 9. Local Step Segments: Step counts imported from system interfaces with precise start and end times as well as data source identifiers for local duplicate cleaning.

B. Legal Basis for Processing

Since storage and evaluation take place exclusively locally on your end device, control over data protection and data processing remains in your own sphere. Insofar as the app is considered within the scope of the GDPR, the following legal bases apply:

• General Data and Settings (Article 6(1)(b) of the GDPR): The processing of general profile settings, training plans, and app preferences is carried out to fulfill the user relationship (provision of app functionalities).
• Health Data (Article 9(2)(a) of the GDPR in conjunction with Article 6(1)(a) of the GDPR): For the processing of physical measurements, heart rate data, sleep analyses, and nutrition logs (which fall under special categories of data as health-related data), you grant your explicit consent by actively entering them or enabling the import. You can withdraw this consent at any time by deleting the corresponding entries or by resetting all app data.

A. Bring-Your-Own-Key (BYOK) AI Meal Capture

Train Libre offers the option to analyze meals via photos or free-text descriptions using artificial intelligence. This function is based on the "Bring-Your-Own-Key" (BYOK) principle. You must store your own API key from a supported provider in the app to use this.

• Supported Providers: OpenAI, Google Gemini, Anthropic Claude, Mistral AI, xAI Grok, Ollama, and custom OpenAI-compatible endpoints.
• Secure Local Key Storage: The API key you enter is stored encrypted using AES-256 encryption via the flutter_secure_storage package in the operating system's secured storage area (iOS Keychain or Android Keystore). The key remains exclusively local to your device and is never transmitted to us.
• Restricted Data Transmission: When using the AI analysis, your device sends the captured meal photo or entered text description directly via an encrypted HTTPS connection to the API of the selected AI provider. No personalized account data, user metadata, or historical profile information from Train Libre is attached to these external endpoint payloads.
• Analytical AI Processing (No Generative Coaching): The AI analysis is used for the exclusive analytical purpose of decomposing meal photos or text descriptions into atomic ingredients. Train Libre does not use AI to dynamically generate or propose personalized recipes, meal plans, or automated health coaching.
• Privacy Protection via System Prompt: To maximize your privacy, the app's globally stored system prompt is configured to instruct the AI provider to identify only food components and estimate their weight in grams. The AI provider is explicitly instructed not to perform any nutrient calculations (such as calories, protein, fat, or carbohydrates). The determination of nutrients is then performed via a hybrid approach: recognized food names are matched against your local offline database using a deterministic Jaro-Winkler-based matching engine (SQLite/Drift).
• Local-First Alignment: Core macro calculations, user profiling, and history tracking remain strictly local-first on your device and are never transmitted to external providers or used to train global AI models.
• Responsibility: Since you are using your personal API key, you enter into a direct user relationship with the respective AI provider. Data processing by the AI provider is subject to their respective privacy policies. Please check your provider's privacy policy (especially regarding the use of data for training purposes and server locations) before using the function.
  
  

  Provider	Privacy Policy
  OpenAI	https://openai.com/policies/privacy-policy
  Google Gemini	https://policies.google.com/privacy
  Anthropic Claude	https://www.anthropic.com/privacy
  Mistral AI	https://mistral.ai/privacy-policy
  xAI Grok	https://x.ai/privacy-policy
  Ollama	https://ollama.com/privacy

  
  For transmissions to providers outside the European Union (especially the USA), this occurs on the basis of standard contractual clauses or adequacy decisions that you have agreed with the provider.

B. Offline Catalog Updates (Open Food Facts & Exercise Catalog)

To scan food barcodes offline and look up exercises, Train Libre uses local product and exercise catalogs. These catalogs are downloaded directly to your device as precompiled SQLite database files.

• How it Works: The app checks at regular intervals whether updates are available for the food catalog (based on Open Food Facts) or the exercise catalog (based on wger/GitHub). The check and subsequent download of the compressed catalog databases are performed via an encrypted HTTPS connection directly to the servers of the hosting service provider (e.g., GitHub Pages / GitHub Inc. or Open Food Facts).
• Data Minimization: When downloading catalog updates, technical connection data (in particular your IP address, date/time of access, and the app's User-Agent) are transmitted to the host as a system requirement. No user-generated data, scanned barcodes, or personal profile characteristics are sent to the catalog hosts at any time.
• Local Barcode Mapping: The matching of a scanned barcode or the search for food and exercises takes place 100 percent offline on your device. Unlike conventional nutrition apps, scanning a product does not send a request with the barcode to a cloud server.

A. Data Import (Reading)

If you grant permission to the app, Train Libre reads data from Apple HealthKit or Google Health Connect to display and process it locally within the app:

• Step Counts: Import of recorded step count segments for offline evaluation.
• Sleep Data: Import of sleep intervals and sleep phases.
• Heart Rate: Import of heart rate samples to calculate local hourly aggregations.

The import is used exclusively for display and local analysis within Train Libre. No transfer of this imported data to external servers takes place.

B. Data Export (Writing & Idempotency)

At your request, Train Libre can export data manually recorded in the app to the system health databases (Apple HealthKit / Google Health Connect):

• Body Dimensions: Export of weight measurements.
• Nutrition and Hydration: Export of consumed nutritional values, calories, and water amounts.
• Workouts: Export of completed training sessions.

Local Idempotency Protection: To prevent duplicate data from being written to your system health database during repeated synchronizations, Train Libre features a local logging system. In the health_export_records table of the local SQLite database, a unique ID, the target platform (Apple Health or Health Connect), the data domain, and a unique idempotency key are stored together with the export timestamp for every successful write operation. This comparison takes place purely locally on your device and serves to ensure data consistency.

A. Local Data Isolation

The operating system (iOS/Android) isolates Train Libre's app data using sandbox mechanisms. Other installed applications do not have access to the local SQLite database or the API keys stored in the secured app settings without your consent.

B. Manual and Automatic Backups

The app offers functions to back up your data in order to prevent data loss in the event of device replacement or damage.

• 1. File Generation and Export: You can generate a complete backup of all data stored in the SQLite database and in the settings. This backup is generated as a structured JSON file in the operating system's temporary storage area and exported via the system's own share menu (Share Sheet). After the export, the temporary file is deleted immediately.
• 2. Encryption: To protect your sensitive data, backups can be encrypted with a password of your choice before export. The encryption is performed locally on the device using strong cryptographic algorithms. Unencrypted backups should always be stored in secure locations.
• 3. Automatic Backups: You can enable automatic backups at configurable intervals. On Android, this feature uses the Storage Access Framework (SAF) to save directly to a target folder selected by you. Alternatively, the file is saved in the local app document directory. These backup files remain on your device unless you actively copy them to an external cloud storage location (e.g., iCloud Drive or Google Drive).
• 4. System Backups: Please note that if system-wide device backups are enabled (e.g., via Apple iCloud or Google Drive Backup), Train Libre's application data will by default be uploaded to the respective cloud by the operating system. This is beyond our control and can be disabled for Train Libre in your device's system settings.