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.

How AI cut weeks of PK/PD analysis into days, enabling faster dose optimization, scalable experimentation, and reduced reliance on specialized pharmacology expertise.

Using time-series clinical data and Neural ODE models to predict patient outcomes, helping life sciences teams improve biomarker discovery and clinical decisions.

How a generative AI platform transformed scattered text data into real-time intelligence- driving smarter HCP engagement, faster decisions, and over $1M in cost savings.

How a custom MLOps platform enabled a pharma company to train, deploy, and monitor hundreds of ML models- without rebuilding their existing infrastructure.

Replacing manual chart review with NLP-driven entity extraction- cutting operational costs and accelerating insights from unstructured medical records.

Aggregating years of siloed interaction data into a single AI hub- unlocking sentiment, trends, and faster action while saving $1M annually.