Manna provides personalized metabolic insights by combining a quarterly over‑the‑counter CGM sensor with daily voice check‑ins and photo food logging. Its physician‑validated AI delivers continuous glucose guidance and coaching, reducing sensor use by 67% while tailoring recommendations to each user’s metabolic response.
Funding
Funding not disclosed
Founders
Product
Problem
People with type 2 diabetes, pre‑diabetes, or elevated metabolic risk often lack affordable, continuous insight into how meals, sleep, stress and hydration affect their glucose levels. Traditional continuous glucose monitoring requires wearing a sensor year‑round, which is costly and burdensome, while diet‑tracking apps provide only calorie data without physiological context.
Solution
Manna combines a quarterly over‑the‑counter CGM sensor with daily 20‑second voice check‑ins and 8‑second photo food logs to create a personalized metabolic profile. The physician‑validated AI engine, Aris, analyzes two weeks of glucose data together with voice‑derived biomarkers (sleep, hydration, stress) to generate evidence‑based recommendations grounded in peer‑reviewed research. After the sensor is removed, the platform continues to deliver real‑time coaching for the following ten weeks, updating its metabolic model each quarter. Users receive transparent explanations of each recommendation, linking specific data points to actionable guidance, enabling them to understand and manage glucose spikes without wearing a sensor continuously.
Target Audience
Primary users are individuals with type 2 diabetes, pre‑diabetes, or metabolic risk seeking affordable glucose insight, as well as health systems and employer wellness programs that aim to reduce chronic disease burden.
Features
- Quarterly OTC CGM (Dexcom Stelo) providing two weeks of continuous glucose data per sensor
- Daily 20‑second voice check‑ins that capture sleep quality, hydration, cortisol and other biomarkers
- 8‑second photo food logging that auto‑extracts meal composition for glucose impact analysis
- Physician‑validated AI (Aris) that maps recommendations to PubMed‑sourced clinical literature
- Transparent recommendation engine showing which data points drive each advice
- Adaptive 12‑week program that recalibrates after each sensor cycle to refine focus areas
- Integration with mobile app for trend visualization, contributor analysis, and alerts