Limbix (by BigHealth)
Evidence-based digital therapeutics for adolescent mental health and behavioral activation.
AI-powered clinical nutrition intelligence and personalized glycemic response modeling.
Nutrino, now integrated into Medtronic’s diabetes division, represents the pinnacle of AI-driven nutrition science. Its technical architecture centers on the 'FoodPrint'—a proprietary digital signature that captures the complex relationship between an individual's biology, activity, and food intake. In the 2026 landscape, Nutrino's technology serves as a critical infrastructure for Continuous Glucose Monitor (CGM) systems, utilizing deep learning algorithms to predict postprandial glucose responses before a user even eats. By processing multi-modal data streams including wearable metrics, historical glycemic data, and a vast, verified nutritional database, Nutrino provides actionable clinical insights. The platform has shifted from a consumer-facing app to a sophisticated B2B 'Nutrition-as-a-Service' (NaaS) model. This allows healthcare providers, insurance companies, and medical device manufacturers to embed high-fidelity nutritional intelligence into their own ecosystems via robust APIs. Its market position is solidified by its clinical validation, moving beyond simple calorie counting into the realm of metabolic digital twins, facilitating precision medicine for chronic disease management.
A proprietary algorithm that creates a personalized digital metabolic signature by cross-referencing food intake with CGM data and physical activity.
Evidence-based digital therapeutics for adolescent mental health and behavioral activation.
Predictive clinical and operational intelligence to fight death and waste in healthcare.
Predictive medical data and clinical insights for streamlined enterprise underwriting.
The professional medical network for clinicians, providing HIPAA-compliant AI and telehealth solutions.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Machine learning models that forecast blood glucose levels for the next 2-4 hours based on planned carbohydrate intake.
Computer vision model trained on over 10 million food images for instant macro-nutrient estimation.
Native protocol support for Medtronic, Dexcom, and Abbott CGM hardware for low-latency data ingestion.
NLP-driven interface for conversational food logging and nutritional advice based on clinical guidelines.
A curated database of over 2 million verified food items with 128 micro/macro-nutrient fields each.
Algorithm that breaks down complex meal descriptions into constituent ingredients to calculate cumulative glycemic load.
Manual carbohydrate counting is often inaccurate, leading to incorrect insulin dosing.
Registry Updated:2/7/2026
Recommendation is sent to the insulin pump controller for bolus adjustment.
Insurance companies lack objective data to reward healthy eating habits.
Clinicians cannot monitor the nutritional compliance of hundreds of patients simultaneously.