Scan product labels and see what every ingredient does
Personal health AI that runs experiments with you and challenges with your friends
Stage
MVP
Not given
Founded
2025
Not given
Based in
US
US
Pricing model
Freemium
Freemium
Pricing
Free: 5 product scans per day. Plus: $4.99 per month with unlimited scans. Pro: $9.99 per month with personalized recommendations and food diary. Yearly plans available with 33% savings.
Free starter usage available. Paid subscription at $8/month with no contract, cancel anytime.
Key features
Barcode scanning for food, drinks, cosmetics, personal care and household products
Plain-English ingredient explanations with evidence tiers
Body map showing which systems each ingredient affects
Product comparison and ranking
Food diary with daily and weekly totals
Personalized recommendations based on health conditions and preferences
Add missing products by photographing the label
NOVA processing score for each product
Personal health conversations via text
Wearable and health data integration
Structured personal health experiments
Group health challenges with friends and family
Photo-based meal logging with automatic tracking
Supplement ordering and appointment booking
Bloodwork analysis and longitudinal tracking
Real browser and phone call automation
Self-hosted open-source option
Connects to wearables, labs, calendar, email and services
What makes it different
Shows ingredient mechanisms rather than single scores, letting users decide for themselves
Evidence-tiered claims that show the quality of research behind each ingredient assessment
Covers cosmetics and household products, not just food
Early access with launch pricing locked in
Education-focused without medical claims or diagnosis
Runs personal health experiments with baseline comparison to test what actually works
Integrates with 20+ wearables, lab services and daily tools
Referees group health challenges with fair baselines across different devices
Automates health tasks like calling dentists and ordering supplements
Open source and self-hostable for complete data ownership
Aurascan
Murph