Household Nutrition · Adaptive Coaching

One meal. Two goals.
Zero manual math.

Not another single-user calorie counter. Fit-Check reads your meals, your wearable, and your household's divergent goals — and splits the math automatically.

Built for couples and families who cook and eat together but train differently — one cutting, one bulking — combining meal recognition, wearable data, and per-person coaching into one adaptive engine.

Try Fit-Check →
2+
Household members, one shared log
4
Wearable ecosystems synced
0
Manual portion math required
The Problem

Shared kitchen. Different goals. No shared tool.

Thousands of nutrition apps exist, and almost none of them assume you cook for more than one person. The friction isn't motivation — it's tools built for a household of one.

01

Logging is tedious

Manual database search, portion guessing, and constant data entry create enough friction that most users stop tracking within weeks.

02

Recommendations are static

A desk day and a marathon-training day get the same calorie target. Fixed plans ignore how life actually varies.

03

Data lives in silos

Wearables capture steps, heart rate, recovery and sleep. Nutrition apps capture food. The two systems never talk to each other.

04

Eating is treated as solitary

Families and couples share meals while needing different nutrition. Existing apps are built for one person, not one table.

Why Now

Four shifts just converged to make this possible.

01
AI understands food
Meals can now be understood directly from a photo or a spoken sentence — no manual database search required.
02
Wearables went mainstream
Apple Watch, Fitbit, Garmin and Whoop now generate continuous health data for a huge and growing share of consumers.
03
Consumers think proactively
Health is increasingly viewed as something to optimize day-to-day, not something to treat only after it breaks down.
04
Governments fund prevention
Public healthcare systems are investing in preventive care to reduce the long-term cost of chronic disease.
Our Solution

One adaptive engine, fed by real life.

Meal recognition and wearable signal feed one continuously adjusting recommendation engine — turning a fixed daily number into a moving target that matches how the day actually went.

Inputs
  • Photo / voice meal log
  • Apple Health
  • Fitbit · Garmin · Whoop
  • Sleep & recovery data
Adaptive Engine

Recalculates calories and macros from today's real activity — not yesterday's static plan.

Output
  • "Increase protein today."
  • "Hydrate after the workout."
  • "Carbs down this evening."
  • One meal, individual portions
Product

Five connected modules.

01

Intelligent Meal Logging

Photo, voice, or barcode input. AI estimates calories, protein, carbs, fats and serving size — tuned for home-cooked, mixed-ingredient meals.

02

Adaptive Nutrition Engine

Daily targets shift with activity, recovery, sleep, weight trend and personal goals.

03

Wearable Intelligence

Syncs Apple Health, Fitbit, Garmin and Whoop — one connection per household member.

04

AI Coaching

Plain-language daily guidance, delivered in-app or via WhatsApp — whichever the user prefers.

05

Shared Nutrition

One shared meal, split automatically into individually personalized portions — for couples, families, teams.

Innovation

Five disconnected systems. One adaptive platform.

We're not building another calorie database — we're building the layer that connects the ones that already exist, learning continuously from behaviour instead of relying on manual input alone.

Market

Starting with consumers, expanding into infrastructure.

Today
Health-conscious consumers seeking sustainable, adaptive nutrition support.
Expansion
Fitness coaching, nutrition professionals, corporate wellness, and family health.
Long-term
An infrastructure layer connecting nutrition data with preventive health monitoring.
Business Model

Freemium today. Enterprise dashboards tomorrow.

Free
Get started
  • Meal logging
  • Nutrition tracking
  • Basic AI recommendations
Premium
Full adaptive experience
  • Unlimited AI analysis
  • Advanced wearable integration
  • Adaptive nutrition engine
  • Shared meal mode
  • Advanced coaching

Future: enterprise dashboards for nutritionists, personal trainers, gyms and corporate wellness providers.

Competitive Landscape

The core is already built. The wedge is what's left.

Fitia, Nutrola and MealThinker already do shared-meal, divergent-goal tracking — that's table stakes now, not a differentiator. Ours is accuracy on real home-cooked meals and a coaching channel people already use.

CapabilityFit-CheckFitiaNutrolaMealThinker
Shared meal, split macros
Home-cooked meal accuracyCore focusGenericGenericGeneric
Wearable sync, per personPartial
WhatsApp-native coaching
DistributionNutritionists & gymsPaid UAPaid UAPaid UA

Benchmarked against Fitia (10M+ users), Nutrola (2M+ users), and MealThinker — the closest household-nutrition competitors, not generic single-user calorie apps.

Go-To-Market

Grow through trust, not ad spend.

We reach users through the professionals and communities they already trust — then let partnerships and referrals compound.

01Nutritionists
02Fitness Coaches
03Gyms
04Universities
05Startup Communities
06Health Influencers
Roadmap

Four phases from validation to scale.

PHASE 1
Discovery
Validate pain points through direct customer interviews.
PHASE 2
Build MVP
Home-cooked meal accuracy, shared meal logging, per-person macro split, wearable sync.
PHASE 3
Beta Launch
Collect behavioural data, measure retention, improve recommendations.
PHASE 4
Commercial Launch
Scale partnerships, expand internationally, build enterprise offerings.
Funding

Raising to build the first production-ready release.

  • Product development
  • AI infrastructure
  • Wearable integrations
  • User validation
  • Clinical & nutritional advisory
  • Go-to-market validation
Long-Term Vision

The operating system for personalized nutrition — connecting food, activity, recovery and behaviour into one intelligence layer.

Let's talk Pre-seed · Berlin · Bootstrapped MVP in progress