Pali offers an enterprise‑grade risk‑management engine for people with Type 1 Diabetes, combining continuous glucose monitor (CGM) data with heart‑rate variability (HRV) to create a predictive, agentic life‑intelligence platform. By continuously fusing these signals, Pali anticipates glucose trends and alerts users before events occur, reducing the 180 daily decisions a patient typically makes. The solution is delivered as a native iOS app currently in a private beta cohort.
Funding
Funding not disclosed
Founders
Product
Problem
People with Type 1 diabetes must interpret continuous glucose monitor (CGM) data and make dozens of treatment decisions each day, leading to high cognitive load and increased risk of suboptimal glucose control.
Solution
Pali provides an iOS‑based Enterprise Risk Management engine that fuses CGM readings with heart‑rate variability (HRV) signals to generate a predictive awareness state. By analyzing these combined biomarkers, the platform forecasts upcoming glucose trends and delivers proactive insights, reducing the number of manual decisions a user must make. The system operates as a “life‑intelligence” layer, continuously monitoring risk and alerting the user before glucose excursions occur. This predictive approach aims to lessen the mental burden of disease management and improve overall glycemic outcomes.
Target Audience
Primary users are individuals with Type 1 diabetes who rely on CGM technology and seek automated, predictive support to manage their condition.
Features
- Native iOS application that integrates directly with compatible CGM devices
- Real‑time fusion of CGM data and HRV metrics to create a unified risk profile
- Predictive algorithms that forecast glucose trends and potential excursions
- Proactive alerts and actionable recommendations delivered to the user’s device
- Continuous risk scoring that abstracts multiple daily decisions into a single awareness state
- Secure data handling with encrypted transmission and storage