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SF

Sugar Fit

The startup provides a cloud‑based mobile platform that consolidates glucose data from continuous glucose monitors and manual entries into a single dashboard. It uses AI‑driven predictive analytics to forecast glucose trends, issue customizable hypo‑ and hyperglycemia alerts, and generate secure, exportable reports compatible with HL7/FHIR for clinician review.

Bengaluru, IndiaFounded 202137150K+ followers
Updated 3 months ago

Funding

$5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.

ES
Funding rounds are not available yet.

Founders

Product

Problem

People with diabetes or metabolic disorders often lack a unified, easy-to-use system for tracking blood glucose data and receiving actionable feedback, which can lead to inconsistent glycemic control and increased risk of complications.

Solution

The platform delivers a cloud‑based mobile application that consolidates glucose readings from compatible continuous glucose monitors (CGMs) and manual entries into a single dashboard. It applies statistical and machine‑learning models to generate personalized insights, such as predicted glucose trends and risk alerts, helping users anticipate and mitigate excursions. Users can set customizable notification thresholds for hypo‑ and hyperglycemia, and the app visualizes daily, weekly, and monthly patterns to support long‑term management. Secure data synchronization enables optional sharing with clinicians or integration into electronic health record (EHR) systems for coordinated care. All data are encrypted in transit and at rest, ensuring compliance with health‑privacy regulations.

Target Audience

The primary users are individuals with type 1, type 2 diabetes, or pre‑diabetes who seek daily glucose monitoring and data‑driven guidance, as well as healthcare providers who require remote patient data for treatment adjustments.

Features

  • Automatic import of glucose data from major CGM manufacturers via Bluetooth and API connectors
  • AI‑driven predictive analytics that forecast glucose trajectories 30‑60 minutes ahead
  • Customizable alerts for out‑of‑range readings, trend deviations, and missed measurements
  • Interactive charts and heat‑maps showing time‑in‑range, variability, and carbohydrate impact
  • Exportable CSV and HL7/FHIR‑compatible reports for clinician review or research use
  • Role‑based access controls and end‑to‑end encryption to meet HIPAA and GDPR standards
  • In‑app educational library with evidence‑based articles and self‑management tools
This profile is AI-generated and may contain inaccuracies.