Healify — AI-Powered Health Companion
Build an AI-driven mobile app that empowers users to improve their health through personalized insights based on their real data.
Goal
Build an AI-driven mobile app that empowers users to improve their health through personalized insights based on their real data.
Outcome
We developed an MVP that successfully raised $2,000,000 in funding, demonstrating both the technical and market potential of the product.
Our Approach
We partnered closely with Healify's founders to turn their idea into a working MVP.
Discovery & Planning
- Collaborated to define detailed technical documentation and feature scope.
- Provided a clear project estimation and delivery roadmap.
Development & Iteration
- As new requirements emerged, we adapted the roadmap to enhance the product's intelligence.
- Integrated multiple AI agents using the LangChain framework to handle diverse health insights.
- Focused on modular scalability to prepare for future features and AI integrations.
AI Architecture
- Created an "AI orchestra" — a system of interconnected agents that continuously refine user data for more accurate recommendations across diet, activity, and wellness.
Team
Rituals:
- Bi-weekly sprints with demos and planning sessions
- Daily check-ins with developers and QA
Key Features
Health Data Integration
Connected with Apple HealthKit to sync data like activity, sleep, and nutrition from iPhones and Apple Watches.
AI Recommendations
Leveraged OpenAI, LangChain, and Pinecone to analyze anonymized health metrics and deliver personalized lifestyle recommendations.
Blood Test Analysis
Enabled users to upload blood test results, which the AI analyzes to refine diet and fitness suggestions.
Smart Meal Planner
Automatically generates meal plans with recipes, grocery lists, and cost estimates tailored to individual health data.
Under the Hood
Tech Stack:
Performance Optimization:
Streamlined backend and API architecture to ensure smooth, responsive user experiences.
AI Experimentation:
Tested multiple model configurations to balance accuracy and cost-effectiveness at scale.
Message Classification System:
We classify each user message to determine whether it's a question, a health-metric update, or a general thought. Based on this classification, the backend decides whether it has enough data from the health-metrics database to generate an answer, needs to request additional input from the user, or should rely on AI to provide a recommendation.
Admin Dashboard:
We built an advanced admin dashboard that allows us to define custom thresholds for different health metrics, enabling more precise monitoring and tailored recommendations.
Result
A fully functional MVP that wowed early investors, validated the product vision, and positioned Healify as a serious contender in the AI wellness space.