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Automating preventive care pathways with AWS- improving patient engagement, risk stratification, and operational efficiency across a leading diagnostic network.
An AI scheduling platform that slashed manual work by 90%, uncovered millions in savings, and boosted EBITDA for a fast-growing home care provider.
Bringing public and proprietary HCP data into one compliant platform- powering therapy-specific insights and laying the foundation for scalable AI initiatives.
How an AI platform delivered personalized engagement at massive scale- predicting adherence risk and guiding targeted interventions for millions of patients.
A patient-facing AI assistant that improved device adoption by answering questions naturally, surfacing trusted content, and revealing real-world care gaps.
Replacing manual chart review with NLP-driven entity extraction- cutting operational costs and accelerating insights from unstructured medical records.
Using early trial data and machine learning to predict Phase 3 outcomes- helping pharma teams advance the right drug candidates with confidence.
How predictive models helped frontline providers identify which patients need outreach- and how to intervene to improve adherence and outcomes.
Identifying who responds to treatment using ML- driving better outcomes, payer partnerships, and published evidence in digital therapeutics.
A HIPAA-compliant mobile app that enabled remote CPAP sizing and intake- processing thousands of patients safely when in-person care wasn’t an option.
Predicting post-discharge care needs using years of hospital data- helping providers reduce readmissions and allocate resources more effectively.
An AWS-powered platform combining AI insights and expert coaching to deliver personalized weight loss, drive engagement, and scale securely.
Digitizing nutrition data for a nonprofit fighting child malnutrition- enabling faster reporting, offline operations, and greater transparency for donors.
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