Fitto: IoT Ecosystem That Powers Smart Supplement Consumption

‍Client Vision

The co-founders of Fitto came to Infinity Technologies with a clear problem — active professionals with busy, high-performance lifestyles often forget or mismanage their nutritional supplement programs. Ari, one of the co-founders, struggled with skipping meals due to his non-stop schedule. Yaniv, his co-founder and a fitness enthusiast, was unable to stick to his supplement plan because of constant commuting and the inconvenience of carrying multiple products.

Their vision was to create a connected ecosystem that uses IoT and AI to automate supplement reminders, track consumption, and optimize nutrition programs based on user behavior — a personal wellness assistant in your pocket, bottle, and wrist.

Business and Product Objectives

The goal was to build an intelligent health companion — a platform combining:

• A smart bottle with trackable capsules
• A smartwatch companion
• A mobile app with cloud sync
• An AI engine for behavior-based supplement recommendations

The system needed to:

• Track daily intake, consumption patterns, and nutritional gaps
• Deliver real-time feedback across devices without user interaction
• Scale to support third-party supplement brands for white-labeling, behavioral analytics, and automated reorders

Solution

Infinity Technologies delivered a complete IoT platform connecting hardware devices, mobile apps, cloud infrastructure, and machine learning components. The ecosystem provides real-time monitoring of supplement intake, syncs data across devices, and generates personalized recommendations using AI models trained on behavioral patterns.

Architecture Overview

The platform was designed as a distributed IoT + AI architecture, consisting of the following layers:

1. Device Layer: Smart bottle with embedded sensors + smartwatch with tracking APIs
2. Mobile Layer: React Native app for iOS and Android
3. Connectivity Layer: Bluetooth Low Energy (BLE) for device communication
4. Cloud Layer: AWS-based microservices architecture with Node.js backends
5. AI Layer: Python-based machine learning engine deployed via serverless architecture

‍

Device Integration & Communication

• BLE Communication: Smart bottle and smartwatch communicate with the mobile app using Bluetooth Low Energy, allowing seamless real-time data transfer with minimal power consumption.
• Device UUID Registration: Each bottle and pod has a unique identifier tracked across cloud and local sync layers.
• Two-way sync: Changes triggered by the app or AI engine can send configuration updates (e.g., reminder intervals, LED light colors) back to the bottle and watch.

Mobile Application

• Developed with React Native, allowing shared codebase across iOS and Android.
• Handles BLE pairing, push notifications, consumption history, AI-based suggestions, and onboarding of new smart pods.
• Local caching and offline-first architecture enable functionality even without immediate cloud access.

Backend Services

• Built using Node.js microservices communicating over REST and secure WebSocket protocols.
• Authentication via Firebase Auth, with session control, token expiration, and role-based access.
• Cloud Firestore and MySQL were used in parallel — Firebase for real-time device state and user interactions, MySQL for long-term analytics, business intelligence reporting, and historical user behavior.

Machine Learning & AI Engine

• Developed in Python using Pandas, scikit-learn, and custom algorithms for:
  • Pattern recognition of supplement adherence habits
  • Behavioral clustering to compare users with similar goals/lifestyles
  • Automated dosage/timing adjustment recommendations
• Models are trained on anonymized user data, with scheduled retraining pipelines.
• Hosted on AWS Lambda functions for low-latency inference and easy scalability.

Cloud Infrastructure

• Entire backend and AI logic are deployed to AWS, with the following services:
  • AWS IoT Core for secure device registration and communication
  • AWS Lambda for serverless logic execution
  • Amazon S3 for storing AI model artifacts and raw sensor data
  • Amazon RDS (MySQL) for relational data
  • AWS API Gateway for REST interface management
  • AWS CloudWatch for logging, health checks, and system monitoring

Security & Compliance

• End-to-end encryption between devices, mobile apps, and cloud (TLS 1.3, AES-256).
• GDPR-compliant data processing with consent-based tracking and local device anonymization.
• Role-based access for users, admins, and brand partners.

Key Features

• Real-time Supplement Tracking: Users are notified when to take capsules, how much is left, and when to reorder.
• Personalized AI Coach: Recommends optimal supplement routines based on activity, dietary data, and past behavior.
• Multi-device Sync: Bottle, smartwatch, and mobile app stay in sync — even offline.
• Business Intelligence for Brands: Nutrition brands receive aggregated insights on consumption patterns, client churn risk, and loyalty triggers.

Business Value Delivered

For users:

• 80% increase in supplement adherence
• 60% reported reduced cognitive load by removing manual tracking
• 90% satisfaction rate with mobile app UX and AI recommendations

For brands:

• Ability to white-label the app and smart pods, expanding digital presence
• Access to real-time consumer behavior data
• Improved retention and upsell via automated replenishment logic

Conclusion

Fitto is a pioneering IoT solution that transforms how health-conscious users interact with nutritional supplements. Through the power of real-time data, AI-driven insights, and seamless device integration, Infinity Technologies helped launch an ecosystem that’s not only intelligent but truly personal.

This case showcases our ability to combine hardware integration, AI modeling, mobile UX, and scalable cloud infrastructure into one unified experience — perfect for healthtech, wellness, smart appliances, and connected consumer goods.

‍