Learn how to use ROOK’s wearable health data to train AI models for personalized health insights. Discover the steps involved, from data collection and cleaning to model training and deployment, and explore how AI can provide actionable health recommendations in real-time.

Wearable data is valuable, but it’s often messy and complex. Learn how a unified API can help normalize wearable data from multiple devices, making it easier to integrate, analyze, and build personalized health apps that empower users and drive better outcomes.

Explore the best tools for building AI health apps with real-world wearable data. Learn about platforms like ROOK API, TensorFlow, and Google Cloud, which simplify integration, enhance data analysis, and provide powerful, personalized health insights for your app.

Wearables are no longer just fitness devices. This article explores how they are becoming continuous health monitoring systems and transforming digital health products.

AI agents in health require more than raw data. This article explains the data foundations—standardization, context, and trust—needed to support reasoning and decision-making at scale.

Wearable data is becoming core infrastructure for digital health. This article explores how standardization, AI, and trust will shape the future of wearable data in 2026 and beyond.

Wearable data is a powerful input for AI in health, but only when handled correctly. This article explains how to prepare, standardize, enrich, and use wearable data to build reliable, scalable AI health models.

Standardizing wearable data is key to building scalable health products. In this article, we explain how to unify data from Fitbit, Apple Watch, and Garmin, and avoid common pitfalls when working with connected health data.

Apple Health and Health Connect are the two main platforms for accessing health data on iOS and Android. In this article, we analyze their pros, cons, and how to integrate with both when building cross-platform health and fitness applications.

Discover the top 10 wearable APIs in 2025 and how they are transforming health and fitness data integration. A practical guide for developers and companies looking to build smarter, more personalized applications powered by real-time data.

Wearables generate continuous health data with enormous potential, yet they remain disconnected from electronic health records. This article explains how AI normalizes, contextualizes, and unifies these signals to create a more integrated ecosystem that supports prevention, personalization, and better clinical decision-making.

Integrating data from multiple wearables into one system is challenging due to fragmented devices, formats, and APIs. This article explains the main approaches, key technical needs, and how a unified platform like ROOK enables normalized, analysis-ready, and AI-ready wearable data.

Health-tech companies are adopting AI to deliver more personalized and predictive experiences. However, success depends on data that is reliable, structured, and continuous. This article explains why AI-ready wearable data is becoming a key competitive advantage and how it helps teams innovate faster.

Developers face growing complexity when integrating health and activity data from wearables. This guide highlights the best wearable APIs available today, compares their strengths, and explains how teams can choose the right solution for scalable, reliable data integration.

Discover the top 10 EHR (Electronic Health Record) systems and why integrating wearable devices into these systems can transform healthcare. Explore how real-time wearable data integration can improve patient monitoring, chronic disease management, and personalized care.

The combination of wearables and artificial intelligence is transforming chronic disease management. These advances enable real-time monitoring, early detection, and more personalized care, creating new opportunities for both patients and healthcare providers.

AI is transforming raw wearable data into regulatory-grade evidence. By cleaning, standardizing, and validating biometric signals, AI turns fragmented sensor streams into reliable insights for clinical trials, digital biomarkers, and real-world evidence. This shift is redefining how pharma generates and uses data for innovation.

AI is transforming wearable data into powerful health insights that are reshaping insurance underwriting. By turning continuous biometric signals into validated risk indicators, insurers can assess risk more accurately, personalize pricing, and build proactive wellness programs that improve customer engagement and long-term outcomes.

Fragmented wearable data limits the true potential of digital health innovation. Disconnected platforms create inefficiencies, poor user experiences, and lost opportunities for businesses. Discover how AI-driven solutions unify data, enhance insights, and unlock the real value of wearables.

Integrating wearable technology into digital health platforms doesn’t just enhance user experience—it drives loyalty. By providing real-time data, personalized insights, and seamless engagement, wearable integrations can increase product retention by up to 25%. Discover how wearables turn everyday health tracking into lasting user commitment.