Built for Health Data Autonomy
Enterprise-grade platform powering continuous monitoring, AI analytics, and patient empowerment.
The Care-Live Intelligence Platform
Three powerful engines work in harmony to transform raw biometric data into actionable health insights.
Health Engine
The Health Engine is the data ingestion and processing core of Care-Live.
- Continuous ingestion of 8 vital biomarkers from Body Pro, ScanWatch, BPM Core, and Sleep Mat
- Multi-variate time-series analysis tracking BP, glucose, weight, heart rate, SpO2, sleep, temperature, and body composition simultaneously
- Signal processing and noise reduction using Kalman filters and wavelet transforms for clinical-grade data accuracy
- Advanced statistical modelling including moving averages, rate-of-change analysis, and percentile ranking against population baselines
- Data fusion from EHR systems, lab results, and patient-reported outcomes for a complete health picture
- Real-time data normalisation and standardisation to account for device variance, patient demographics, and measurement conditions
AI Automation Engine
The AI Automation Engine powers intelligent monitoring, early detection, and clinical decision support.
- Deep learning LSTM and Transformer models process continuous time-series data to detect subtle biomarker deviations
- Multi-modal anomaly detection combining isolation forests, autoencoders, and Gaussian mixture models for early risk identification
- CKM progression prediction using ensemble methods — gradient boosting, random forests, and neural networks working together
- Predictive risk scoring with AUC >0.92 for Stage 2+ CKM progression, validated against clinical cohorts
- Automated alert triage with severity classification, escalation protocols, and smart notification routing to care teams
- Natural language generation produces clinical summary reports and trend explanations for healthcare providers
Personalised Recommendation Engine
The Recommendation Engine transforms AI insights into tailored, actionable care plans.
- Patient similarity matching using collaborative filtering to identify effective interventions from comparable successful cases
- Reinforcement learning optimises care plan adjustments over time, learning what works best for each patient
- Dynamic care plan generation incorporating CKM stage, comorbidities, lifestyle factors, medication history, and patient goals
- Behavioural nudging and adherence optimisation using gamification, reminders, and personalised health coaching messages
- Outcome tracking and feedback loops continuously refine recommendations based on patient response data
- Clinician-in-the-loop design ensures every AI recommendation is reviewable, adjustable, and auditable by healthcare providers
How the Three Engines Work Together
The engines operate as a unified intelligence pipeline.
Ingest & Process
The Health Engine ingests continuous biometric streams from Withings devices, normalises the data, and enriches it with EHR and contextual information.
Analyse & Predict
The AI Automation Engine analyses the processed data using deep learning models, detects anomalies, predicts CKM progression, and generates risk scores.
Personalise & Act
The Recommendation Engine converts AI insights into tailored care plans, delivers personalised interventions, and tracks outcomes to continuously improve.
The result: a closed-loop system where data flows seamlessly from monitoring to insight to action — empowering clinicians to deliver precision care at scale.
Cloud-Native Architecture
Built on modern cloud infrastructure for scalability, reliability, and security. Microservices architecture with auto-scaling, multi-region redundancy, and 99.99% uptime SLA.
Enterprise-Grade Security
AES-256 encryption at rest and in transit. HIPAA, GDPR, and PDPO compliant. Role-based access control, multi-factor authentication, and regular penetration testing.
Machine Learning Stack
TensorFlow, PyTorch, and scikit-learn pipelines. Continuous model training, A/B testing, explainable AI with SHAP/LIME, and clinical validation protocols.