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CASE STUDY

Bevel

AI-powered personalized health and wellness companion that turns wearable and lifestyle data into actionable insights.

Industry Health & Wellness / Digital Health
Solution AI Personal Health Intelligence Platform
Engagement 6 Months
Services AI & Full Stack Development
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Bevel

Bevel is a New York-based health technology company developing an AI health companion app that synthesizes wearable, lifestyle, and biometric data into personalized health insights and recommendations. It integrates with Apple Health and other data sources to help users understand patterns in sleep, activity, nutrition, and stress, empowering them to make informed wellness decisions.

The company has grown rapidly since its 2023 launch, raising funding to scale its software-based health intelligence engine and attracting a growing user base in the U.S. with high engagement metrics and broad data adoption across popular wearable platforms.

AI-Driven Health Companion
Wearables & Lifestyle Data Integration
U.S. Health & Wellness Adoption

The Challenge

Enable an AI-based personalized health engine capable of interpreting varied biometric and lifestyle data sources (sleep, recovery, nutrition, stress, activity) to generate actionable insights that improve long-term engagement, adherence, and wellness outcomes across diverse user profiles.

Our Solution

We designed and built an AI health intelligence layer that ingests wearable and lifestyle data, trains multi-modal health pattern models, and delivers personalized metabolic and wellness insights through real-time inference, contextual scoring, and adaptive recommendation logic tied into user dashboards and routines.

Wearable & Lifestyle Data Pipelines

Secure ingestion and normalization of diverse biometric sources.

Health Pattern Recognition Models

AI models predicting recovery, performance, and metabolic states.

Adaptive Recommendations

Personalized guidance on sleep, activity, nutrition, and stress.

Real-Time Inference Engine

Low-latency model execution with privacy-focused backend.

How We Delivered

1

Discovery & Alignment

Mapped multi-source data use cases and defined personalization objectives.

2

Architecture & Planning

Designed secure, scalable data pipelines and model workflows.

3

Engineering & Integration

Built ingestion, modeling, and real-time recommendation services.

4

Testing & Validation

Validated model relevance, privacy safeguards, and UI experience.

5

Deployment & Support

Production release with performance monitoring and iterative tuning.

Outcomes Delivered

38% Increase in Daily Active Usage

Personalized insights and adaptive recommendations significantly improved daily engagement and habit adherence.

27% Improvement in Sleep & Recovery Consistency

AI-driven pattern recognition supported measurable improvements in user sleep and recovery metrics.

45% Higher Recommendation Interaction Rate

Users engaged more frequently with personalized metabolic and wellness suggestions.

99.9% Platform Reliability

Secure, real-time inference infrastructure maintained high availability during rapid user growth.

Facing a Similar Challenge?

If you’re building an AI-enabled personal health or wellness platform with real-time recommendations from wearable and lifestyle data, we can help design, build, and scale it.