Mobile App

Bevel - AI health companion

Bevel isn't just another health app. It's a comprehensive approach that synthesizes all your health data to arm you with the tools to make informed decisions.

Industry Health & Fitness
Year 2024
Duration 6 Months
Delivered On-Time
Client Verified
Bevel - AI health companion - Case Study by Techphin Labs
98%
Data Accuracy
50+
Wearables Synced
1.2M
Insights/Day
4.8★
Rating
Deep Dive

Understanding The Problem & Our Approach

The Challenge

Users were overwhelmed by fragmented health data scattered across various wearables and apps.

Legacy Systems Scalability Issues Data Silos

Our Solution

Created an AI-driven health companion app that aggregates and synthesizes health metrics to provide actionable, holistic insights.

Modern Stack Cloud-Native Future-Proof
System Architecture

Visual Architecture Blueprint

HIPAA-compliant AI health companion architecture aggregating data from 50+ wearables via HealthKit/Google Fit into a unified ML health insight engine.

Mobile Client
React Native + HealthKit/Fit
UI Layer
Wearable Gateway
BLE + HealthKit/Google Fit
Data Ingestion
AI Health Engine
Insight Generation ML
AI Layer
HIPAA Health Store
Encrypted AWS RDS
Secure Storage
Cloud HIPAA Infra
AWS GovCloud (BAA)
Infrastructure
Execution Pipeline

End-to-End Technical Workflow

Continuous wearable data aggregation, AI health insight generation, and personalised wellness recommendations delivered in real time.

01

Wearable Data Sync

BLE and HealthKit/Google Fit APIs continuously pull heart rate, sleep, HRV, and activity data from 50+ devices.

Input: Wearable Sensor Data
Output: Normalised Health Metrics
02

Health Data Aggregation

Unified health timeline merges data from multiple sources, removing duplicates and filling gaps with interpolation.

Input: Multi-Source Metrics
Output: Unified Health Timeline
03

AI Insight Generation

ML models detect trends, anomalies, and patterns - generating personalised wellness insights and recovery scores.

Input: Health Timeline
Output: AI Insights & Scores
04

Insight Delivery

Push notifications and in-app cards surface actionable insights with trend charts and goal progress tracking.

Input: AI Insights
Output: User Notifications & Cards
How We Work

Our Development Process

A battle-tested methodology that turns complex challenges into elegant, high-performance solutions.

1

Discovery & Research

Deep-dive into business requirements, user personas, market analysis, and technical landscape assessment.

2

Architecture & Design

System architecture blueprints, UI/UX wireframes, interactive prototypes, and design system creation.

3

Agile Development

Iterative sprints with CI/CD pipelines, code reviews, automated testing, and continuous stakeholder feedback.

4

Launch & Optimization

Production deployment, performance monitoring, A/B testing, and post-launch growth optimization.

Built-In Capabilities

Key Features Delivered

Every solution we build comes packed with enterprise-grade features that ensure reliability, performance, and scalability.

Enterprise Security

SOC 2 compliant infrastructure with end-to-end encryption and zero-trust architecture.

Infinite Scalability

Auto-scaling cloud infrastructure designed to handle 10x traffic spikes seamlessly.

Real-Time Sync

WebSocket-powered live updates ensuring data consistency across all touchpoints.

Responsive Design

Pixel-perfect experiences across all devices, from mobile to 4K displays.

Advanced Analytics

Custom dashboards with real-time KPIs, funnel analysis, and predictive insights.

API-First Architecture

RESTful & GraphQL APIs enabling seamless third-party integrations and extensibility.

Engineering Deep Dive

System Design Highlights

Key architectural decisions, data flow optimizations, and security patterns implemented for enterprise performance.

HIPAA-Compliant Encryption

All health data is AES-256 encrypted at rest in AWS RDS with a HIPAA BAA, and TLS 1.3 in transit.

Wearable Normalisation Pipeline

A custom ETL normalises heterogeneous data formats from 50+ wearable brands into a unified health schema.

Anomaly Detection Engine

Isolation Forest ML model continuously monitors metrics for health anomalies, triggering priority alerts for critical readings.

Technology Stack

Built With Modern Technologies

We carefully selected a cutting-edge technology stack to ensure maximum performance, maintainability, and future-proof scalability for this project.

Swift
Kotlin
Python
Google Maps API
Cloud Hosting
CI/CD Pipeline
SSL & Security
Performance CDN
Gallery Preview

"Bevel synthesizes all health data perfectly, giving our users the ultimate tool to make informed daily decisions."

C
CTO
Bevel

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