B

Zero-Knowledge Age Verification SDK

3.05

Derivation Chain

Step 1 Conflict between age verification and data protection
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Step 2 Operators of services requiring age verification
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Step 3 Privacy-preserving age verification middleware

Competitor references

No usable source links are available for this idea. Its signal notes and scores need independent verification.

Problem

Korean online service operators in gaming, alcohol, and adult content (mid-size Platforms, 10–50 employees) requiring age verification face per-transaction costs of 50–100 KRW ($0.04–$0.08) for identity verification API integration (e.g., PASS) plus personal data retention obligations from collecting resident registration numbers. At 1 million verifications per year, costs reach 50–100 million KRW ($37,500–$75,000), plus liability risk from personal data breaches.

Solution

A zero-knowledge proof (ZKP)-based age verification SDK that confirms only whether a user is 19+ without exposing their actual date of birth to the service. (1) One-time identity verification generates a ZKP token, (2) the service only validates the token (no personal data storage), (3) adapters provided for existing PASS/Kakao verification integration.

Target: Development teams at mid-size online Platforms (10–50 employees) serving age-restricted content
Revenue Model: API call Billing at 30 KRW ($0.02) Per Transaction (40–70% savings vs. traditional verification), minimum monthly fee of 50,000 KRW ($37.50). Volume discount to 20 KRW ($0.015) Per Transaction above 1 million calls/month
Ecosystem Role: Infrastructure
MVP Estimate: 1_month

NUMR-V Scores

N Novelty
4.0/5
U Urgency
3.0/5
M Market
3.0/5
R Realizability
2.0/5
V Validation
4.0/5
NUMR-V Scoring System
N Novelty1-5How uncommon the service is in market context.
U Urgency1-5How urgently users need this problem solved now.
M Market1-5Market size and growth potential from proxy indicators.
R Realizability1-5Buildability for a small team with realistic constraints.
V Validation1-5Validation signal quality from competition and demand data.
Each dimension is scored 1-5 and weighted into grade S/A/B/C/D.
N=.15 U=.20 M=.15 R=.30 V=.20

Feasibility (56%)

Tech Complexity
24.7/40
Data Availability
19.4/25
MVP Timeline
12.0/20
API Bonus
0.0/15
Feasibility Breakdown
Tech Complexity/ 40Difficulty of core implementation stack.
Data Availability/ 25Practical availability and cost of required data.
MVP Timeline/ 20Expected time to ship a usable MVP.
API Bonus/ 15Bonus for viable public API leverage.
Total 100 points; below 50% is filtered out.

Market Validation (70/100)

Competition
10.0/20
Market Demand
20.0/20
Timing
14.0/20
Revenue Signals
12.0/15
Pick-Axe Fit
10.5/15
Solo Buildability
3.0/10
Validation Breakdown
Competition/ 20Signal quality from competitor landscape.
Market Demand/ 20Demand proxies from search and mention patterns.
Timing/ 20Fit with current shifts in tech, behavior, and regulation.
Revenue Signals/ 15Reference evidence for monetization viability.
Pick-Axe Fit/ 15How well the concept serves participants in a trend.
Solo Buildability/ 10Practicality for lean-team implementation.
Total 100 points; below 50 is filtered out.

Technical Requirements

Backend [high] Frontend [low] Infrastructure [medium]
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