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CASE STUDY

Noom

AI-powered personalized habit coaching engine for health and weight management.

Industry Healthtech / Digital Wellness
Solution AI Habit Coaching & Personalization Engine
Engagement 6 Months
Services AI Architecture, Model Integration & Full Stack Development
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Noom

Noom is a leading American digital health and behavior-change platform that combines psychology-based coaching with technology to help users build healthy habits and manage weight and wellness goals. The platform leverages personalized programs, real-time feedback, and human coach support to guide sustainable behavior change.

Noom has seen substantial adoption and revenue growth over the years, generating hundreds of millions in revenue and serving millions of users worldwide through its subscription-based mobile app focused on behavioral lifestyle changes and persistent engagement.

Behavioral Health & Habit Coaching
AI-Enhanced Personalization
USA & Global User Base

The Challenge

Noom sought to evolve its behavior change and coaching platform by implementing an AI-powered coaching engine capable of translating user activity, engagement, and self-reported data into personalized guidance, tailored lesson flows, and adaptive recommendations — all while maintaining compliance, scalability, and high performance for mobile and backend services.

Our Solution

We designed and built a full end-to-end AI coaching engine that ingested user behavior data, engineered features, trained personalization models, and integrated adaptive habit recommendations into core backend and mobile interfaces. Continuous model monitoring, bias safeguards, and retraining pipelines ensured accurate, fair, and responsive guidance for diverse user profiles.

AI Architecture & Data Ingestion

Scalable pipelines to capture, clean, and preprocess user behavior and engagement signals.

Feature Engineering & Modeling

Machine learning models to predict habits, preferences, and risk of drop-off.

Backend Integration & APIs

Connected model outputs with core application backend and user interfaces.

Retraining & Monitoring

Automated performance logging, bias checks, and continuous model updates.

How We Delivered

1

Discovery & Alignment

Deep dive into behavior science goals, data availability, and system architecture.

2

Architecture & Planning

Designed backend, data pipelines, and AI modeling workflows.

3

Engineering & Integration

Model development, API integration, and scalability tuning.

4

Testing & Validation

Model accuracy validation and performance testing.

5

Deployment & Support

Production rollout with monitoring, retraining and maintenance.

Outcomes Delivered

28% Increase in User Retention

AI-personalized coaching journeys improved sustained engagement compared to static content flows.

35% Improvement in Habit Adherence

Adaptive habit recommendations increased measurable goal completion rates.

2M+ Active Users Supported

Scalable AI infrastructure supported millions of concurrent wellness journeys.

99.95% Platform Reliability

High-availability backend ensured uninterrupted coaching and real-time personalization.

Facing a Similar Challenge?

If you’re building an AI-powered personalized wellness or behavior-change platform that drives measurable engagement and retention, we can help design and scale it.