Aevia reads your biometrics and tells you exactly what to order next — before you have to think about it.
Aevia connects your biology to food that is available right now. Not through willpower. Through intelligence.
Reads your wearable continuously. Active calories burned, HRV, sleep score, glucose when available. Knows your metabolic state at this exact moment, not yesterday's average.
Target minus current equals exactly what your body needs now. Matches that real-time gap against every available menu item within delivery range. Scores each match 1–100.
Surfaces top three matching meals from Uber Eats or DoorDash. One tap to order — no app switching. The $0.99 intelligence fee is charged only when you order, never for browsing.
Every layer is proprietary. The intelligence core cannot be assembled from off-the-shelf APIs. It requires training on order behavior and biometric correlation.
HealthKit SDK · Steps · Calories · HR · Sleep
Terra API · HRV · Recovery · Strain score
Terra API · Training load · VO2max
Past 90 days on grant · Orders · Macros · Times
Static at onboarding · Goals · Allergies · Prefs · Tier
Dexcom / Libre · Real-time glucose
Real-time sync · Terra API · HealthKit · Updates every 15 min
Avg daily cals · Macro ratios · Time-of-day patterns · Activity norms
Goals · Allergies · Preferences · Dietary tier · Plan type
Nutritionix · USDA FoodData · Vision CV model · Macro extraction
Uber Eats · DoorDash · Any local restaurant in range · Real-time menu + ETA feed
AC Kitchen · Sakara Life
Thistle · Factor · Trifecta
Local premium prep partners
Instacart · Amazon Fresh
Whole Foods · Phase 2
Sweetgreen · Chipotle
Real-time via Nutritionix
500+ chains indexed
Employer wellness · Clinics
White-label Phase 3
Aevia serves anyone who orders food regularly and wears a device. The intelligence layer adapts to how they live — whether they're ordering through Uber Eats on a Tuesday or getting chef-prepared meals delivered weekly.
Two women in Miami. Both in their mid-30s. Both health-conscious. But different body types, different sleep patterns, different metabolic needs — and Aevia knows the difference from day one.
No manual logging. No decision fatigue. Aevia works in the background and surfaces the right recommendation at the right moment.
Sleep score 68. HRV below baseline. Recovery debt flagged. The intelligence engine adjusts today's macro targets to support recovery — less aggressive on training nutrition, higher on anti-inflammatory foods.
Post-workout recovery window. The engine calculates protein and carbohydrate requirements for muscle protein synthesis within the next 45 minutes. The window is real and time-bound.
On track for calories and carbs. Protein still 40g short of daily target. Recommendation shifts to high-protein, lower-calorie source with minimal friction.
Daily summary: 200 calories short, 30g protein remaining, zinc and magnesium gap. The engine matches against a local Thai restaurant via computer vision and USDA mapping.
Each model represents a different philosophy on monetization. Toggle to see revenue projections, unit economics, and the strategic tradeoff each one makes.
The user pays only when they act on a recommendation. Zero friction to start. Revenue directly tied to product value. Monetizes behavior that already exists.
Free tier builds the dataset and habit. Conversion happens naturally when the user taps "Order." No sales funnel required.
One price. Unlimited recommendations. Aligns with the Aevia brand — "longevity clinic in Tribeca" patients think in monthly retainers, not microtransactions.
Higher commitment barrier up front. Best for performance and clinical ICP rather than mass-market casual users.
Maximizes market width. Free tier captures users. Per-order fee monetizes them the moment they act. Premium ($29.99/month) unlocks performance mode and removes per-order friction.
Launch with per-order only. Add premium at Month 6 once the habit is proven. The most defensible long-term structure.
| DoorDash GOV 2024 | $80.2B | +20% YoY |
| Uber Delivery 2024 | $74.6B | +17% YoY |
| Global online food delivery 2024 | $430B | — |
| CAGR 2024–2029E | +9.5% | → $680B by 2029 |
| US market 2029E | $236B | +52% from now |
| Digital nutrition market 2024 | $28B | — |
| CAGR 2024–2030E | +15.2% | → $65B by 2030 |
| Wearable health device users | 450M+ | +22% YoY |
| MyFitnessPal users | 220M | ~$350M ARR |
| Noom peak ARR | $500M | declining |
No platform currently connects real-time biometric data to purchasable food at the moment of the food decision.
Every competitor has one or two of these capabilities. Aevia is the only platform designed to have all four.
| Capability | AEVIA | MyFitnessPal | Noom | DoorDash | Uber Eats |
|---|---|---|---|---|---|
| Real-time biometric ingestion | ✓ | — | — | — | — |
| Nutritional gap calculation (live) | ✓ | partial | — | — | — |
| Restaurant menu macro extraction | ✓ | ✓ | — | — | — |
| In-app ordering (not a redirect) | ✓ | — | — | ✓ | ✓ |
| Recommendation tied to current body state | ✓ | — | — | — | — |
| Longevity / clinical tier | Phase 2 | — | partial | — | — |
Miami first. We build the dish database, map the prep meal landscape, and launch with real infrastructure — not a prototype. The market is already here.
25 years building and exiting. Quigo ($380M exit to AOL). Taboola ($2.6B IPO). ConvertMedia ($100M exit). Dapper ($70M exit to Yahoo). Two companies founded. $100M+ raised. Builds AI agents and production systems. Operator-first.
React Native + Node.js. API aggregation and marketplace logistics experience. Has shipped consumer apps at scale. Health tech or wearables background preferred.
Computer vision and NLP. Builds the food recognition and macro extraction model — the proprietary core that cannot be replicated with off-the-shelf APIs alone.
RD or PhD. Designs the gap algorithm logic. Owns dietary profile system. Translates clinical nutrition science into product rules.
Aevia is raising $500K–$750K to build the MVP, launch in Miami, and prove 60%+ recommendation-to-order conversion before expanding.