At FITS AI, we aim to empower healthier food choices by providing:

• 📊 Nutritional Insights: Detailed nutritional facts for packaged food products.
• 🤝 Personalized Health Analysis: Tailored recommendations based on your allergies and health conditions, especially for people managing diabetes.
• 🎯 Health Grades: Products are evaluated and graded from A (healthiest) to D (lowest) to make your decision-making effortless.

Our mission is to support healthier lifestyles through transparency and technology.

Learn more on our project plans.

Our work spans multiple departments, each contributing to our mission of healthier food choices:

• Mobile App: A Kotlin-based mobile application for accessing nutritional facts and personalized health recommendations.

• Backend API: The backend API that powers our app, ensuring seamless data flow and integration.
• LLM Model API (Collaborative with Machine Learning): Deployment and API development for the LLM model on Google Cloud Run.

• Bounding Box Model: A Model for Object Detection to identify and locate nutrition facts table.
• Grades Classifier Model: A machine learning model for assigning health grades (A–D) to products.
• LLM Model: A large language model for analyzing and generating insights related to food products.

Explore all our repositories here.

We are a dedicated group of learners and developers passionate about creating impactful solutions. Meet our team members:

Feel free to explore our repositories and projects for more insight into our work!

Our projects are built using a diverse range of tools and technologies tailored to each department:

• Development Environment: Android Studio
• Libraries & Frameworks:
  • Retrofit
  • Android Jetpack
  • CameraX
  • GSON Converter
• Programming Language: Native Kotlin
• Design Tools: Figma

• Cloud Services:
  • Compute Engine (VM to deploy API)
  • Cloud SQL (Cloud Database)
  • Cloud Storage (For storing objects such as images)
  • Cloud Run (Serverless to run Docker containers)
• Containerization & DevOps:
  • Docker (Containerizing ML models)
  • GitHub (Version Control System & Workflow)
• Programming & Frameworks:
  • JavaScript (Programming Language for API)
  • Python (Programming Language for LLM API)
  • NodeJS (JavaScript Runtime Environment)
  • Express (Framework to build REST API)
  • FastAPI (Framework to build REST API w/ Python)
• Text Editor: Visual Studio Code

• Programming Environment:
  • Visual Studio Code
  • Google Colab
  • Jupyter Notebook
• Programming Language: Python
• Libraries & Frameworks:
  • TensorFlow
  • CV (Computer Vision)
  • Keras (For Building Model)
  • TFLite
  • PyTorch
  • Transformers (Large Language Model)
• Hardware Acceleration:
  • CUDA (Parallel GPU Computing to achieve faster prosessing)
  • cuDNN (Library for optimize Deep Learning)
  • TensorRT (High-performance Deep Learning inference Engine)

Special thanks to our team and the open-source community for inspiration and support.
Built with ❤️ using cutting-edge technologies.