Tio Health: AI Wellness
Transforming pediatric wellness through AI-powered child development tracking and health monitoring. Our engineering focused on integrating the OpenAI Assistants API v2 with a local-first Flutter architecture, providing parents with a secure, highly personalized, and intelligent health companion.
Single-codebase iOS/Android
Deployment
Global mobile healthcare
Reach
Challenge & Scope
Requirements
Combining complex AI conversational flows with sensitive child health tracking
Ensuring total data privacy for pediatric records via local-first persistent storage
Optimizing AI context for highly specific child age and development milestones
Managing dynamic content delivery across platforms without frequent app updates
Strategic Objectives
Create an AI-driven pediatric health companion for parent support and developmental tracking.
Key Deliverables
Technical Execution
Context-Aware AI Assistant
Utilized the OpenAI Assistants API v2, custom-tuning the context to provide parents with accurate, age-appropriate developmental guidance and health logic.
Hardened Local Storage
Designed a local-first storage architecture using Hive and Secure Storage to ensure sensitive milestones and health logs never leave the device unless authorized.
Dynamic Content Sync
Integrated Contentful as a headless CMS, enabling healthcare specialists to update pediatric content and milestones in real-time across the global app base.
Technical Stack
Mobile
Flutter
Dart
Riverpod
AI Integration
OpenAI Assistants API v2
NLP
Storage / Security
Hive
Flutter Secure Storage
Local-First
CMS
Contentful Headless
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Features & Outcomes
AI Pediatrist
Immediate parent support for development-related Q&A.
Milestone Vault
Secure, private tracking of crucial child growth points.
Multi-Child Support
Personalized developmental tracks for every child in the family.
Client Benefits
Cost-effective single-codebase development for global iOS/Android reach
Immediate competitive advantage through cutting-edge AI feature integration
Mitigated technical and legal risks in sensitive health data management
Fast iteration cycles for developmental content without app store delays
Strategic Outcomes
Significantly increased parent confidence through verified AI-powered health support
Ensured elite-level data privacy for sensitive pediatric records via local-first design
Delivered a highly personalized user experience across diverse child developmental paths
Enabled rapid content scaling for health providers via headless CMS integration
System Interfaces
Project Team
Keber
Developer
Flutter Architecture & AI Integration
Project Owner
Technical Lead
Pediatric Data Logic & Security