LeanTaaS
Optimizing healthcare capacity through predictive analytics and AI-driven prescriptive workflows.
Make diabetes suck less with automated data logging and FDA-cleared bolus calculations.
mySugr is a sophisticated Software as a Medical Device (SaMD) platform that serves as a central hub for diabetes data management. Architected to integrate seamlessly with Roche's Accu-Chek hardware ecosystem, the platform leverages proprietary algorithms to estimate HbA1c levels based on longitudinal blood glucose data. By 2026, mySugr has solidified its position as a market leader by utilizing machine learning to provide predictive glycemic insights and personalized feedback loops for users. Its technical infrastructure is designed for high-integrity data ingestion from various IoT medical devices (glucometers, CGMs, and insulin pumps) via Bluetooth and cloud-to-cloud APIs. The application is FDA-cleared and CE-marked, adhering to rigorous clinical safety standards. Its market position is unique, bridging the gap between consumer-grade wellness apps and clinical-grade medical monitoring systems. The technical stack focuses on interoperability, supporting Health Kit and Google Fit, while maintaining strict GDPR and HIPAA compliance for sensitive health telemetry. For healthcare providers, the platform enables data-driven clinical decision-making through standardized PDF/Excel reporting and remote monitoring capabilities.
An FDA-cleared algorithm that calculates insulin doses based on carb intake, current glucose, and active insulin (IOB).
Optimizing healthcare capacity through predictive analytics and AI-driven prescriptive workflows.
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Uses a rolling 90-day mean glucose algorithm to predict clinical lab results with high correlation.
A tag-based indexing system for logs that allows users to query specific glycemic events (e.g., 'pizza', 'exercise').
Integration of visual metadata with glucose logs to assist in retrospective carb counting analysis.
A high-fidelity reporting module that generates clinical-standard data visualizations.
Database-driven logging of oral medications and insulin types with dosage reminders.
Bluetooth Low Energy (BLE) stack optimized for low-latency synchronization with medical peripherals.
Eliminates human error in calculating mealtime insulin doses.
Registry Updated:2/7/2026
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Consolidates fragmented data into actionable medical insights for doctors.
Identifying specific foods that cause unpredictable glucose spikes.