SNAQ
by SNAQ AG
Claims to be the only consumer nutrition app with published, peer-reviewed clinical evidence (4 studies) backing its accuracy and outcomes, rather than self-reported statistics alone.
✓ Last verified July 2026
What it is
An AI nutritionist that identifies calories, carbs, protein, fat, and fiber from a meal photo, then predicts glucose response using the user's own metabolic patterns — proactively suggesting meals and detecting patterns, with an "ask anything, any time" AI nutritionist chat. It integrates with 20+ devices (Dexcom, FreeStyle Libre, Apple Watch, Whoop, Garmin, Polar, Withings, Samsung Health, OneDrop, OneTouch) and serves CGM users, non-CGM users, and GLP-1 medication users. The company states it's backed by 4 peer-reviewed clinical studies (+6.6% Time in Range, −38% carb-estimation error, −6.3% Time Above Range). Free to download, CGM not required premium tier exists but pricing wasn't disclosed. The diabetes-specific app functionality is US-limited 300K+ members worldwide overall.
Key features
- AI meal-photo recognition with personal glucose-response prediction
- "Ask anything, any time" AI nutritionist chat
- 20+ device integrations (Dexcom, Libre, Oura-class wearables, glucometers)
- Serves CGM, non-CGM, and GLP-1 users
- Published peer-reviewed clinical validation
Best for
CGM, non-CGM, and GLP-1 users who want AI meal analysis backed by published clinical research, without requiring a specific device.
Pricing
Free to download, no CGM required premium tier mentioned but pricing not disclosed on-site.
Integrations
- Dexcom
- FreeStyle Libre
- Apple Watch
- Whoop
- Garmin
- Polar
- Withings
- Samsung Health
- OneDrop
- OneTouch
Useful for
Other cgm & metabolic programs
Combines CGM data specifically with GLP-1 dose-titration support and nationwide medication home delivery — a tighter medication+device integration than most CGM-only competitors.
Pulls in sleep, HRV, recovery, and strain data from Oura Ring/WHOOP alongside glucose readings, so the AI coaching accounts for recovery state, not just food and glucose.
Predicts a meal's blood-sugar impact before you eat it, rather than only reporting the response after the fact, and extends the same engine into clinician-facing tools.