Food Additive Health Check for 50s

3.45

Derivation Chain

Step 1 Food health public data API

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Step 2 Increased health food interest among people in their 50s

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Step 3 Problem of not knowing which additives are problematic for one's health condition even after reading the ingredient label at the supermarket

Problem

Chronic disease patients in their 50s with hypertension, diabetes, kidney disease, etc., need to check sodium, sugars, potassium, and phosphorus content when purchasing food. However, the general 'sodium 2000mg or less' standard is for healthy adults, and stricter standards apply to chronic disease patients, but no service informs them of this.

Solution

When users register their chronic conditions (hypertension, diabetes, kidney disease, etc.), scanning a food barcode or photographing the ingredient label shows a 'Safe/Caution/Risk' assessment based on their specific condition. If risky ingredients are found, it recommends alternative foods and tracks cumulative daily intake.

Target: Chronic disease patients aged 48-62 (hypertension, diabetes, kidney disease), users who do their own grocery shopping

Revenue Model: Free for 10 scans per month, unlimited scans + daily intake tracking + personalized alternative food recommendations for 2,900 KRW/month (approx. $2.20).

Ecosystem Role: Education

MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty

3.0/5

U Urgency

4.0/5

M Market

4.0/5

R Realizability

3.0/5

V Validation

4.0/5

NUMR-V Scoring System

N Novelty	1-5	How uncommon the service is in market context.
U Urgency	1-5	How urgently users need this problem solved now.
M Market	1-5	Market size and growth potential from proxy indicators.
R Realizability	1-5	Buildability for a small team with realistic constraints.
V Validation	1-5	Validation signal quality from competition and demand data.

N=.15 U=.20 M=.15 R=.30 V=.20

Feasibility (59%)

Tech Complexity

24.0/40

Data Availability

15.0/25

MVP Timeline

20.0/20

API Bonus

0.0/15

Feasibility Breakdown

Tech Complexity	/ 40	Difficulty of core implementation stack.
Data Availability	/ 25	Practical availability and cost of required data.
MVP Timeline	/ 20	Expected time to ship a usable MVP.
API Bonus	/ 15	Bonus for viable public API leverage.

Market Validation (56/100)

Competition

8.0/20

Market Demand

6.2/20

Timing

14.0/20

Revenue Signals

10.5/15

Pick-Axe Fit

10.5/15

Solo Buildability

7.0/10

Validation Breakdown

Competition	/ 20	Signal quality from competitor landscape.
Market Demand	/ 20	Demand proxies from search and mention patterns.
Timing	/ 20	Fit with current shifts in tech, behavior, and regulation.
Revenue Signals	/ 15	Reference evidence for monetization viability.
Pick-Axe Fit	/ 15	How well the concept serves participants in a trend.
Solo Buildability	/ 10	Practicality for lean-team implementation.

Technical Requirements

Backend [medium] Frontend [medium]

Dashboard