Celebrity Appearance Risk Pre-screening

3.40

Derivation Chain

Step 1 Rapid rise and fall of broadcast talent popularity (e.g., Yang Sang-guk, Seol Woon-do)

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Step 2 Demand for talent risk management among broadcasting and advertising production companies

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Step 3 Automated screening service for talent reputation risk

Problem

When small advertising agencies (5-30 employees) and broadcasting production companies cast models or talent, manually searching for past controversies, legal issues, and social media sentiment takes 2-4 hours per case. If a controversy erupts after contract signing due to missed verification, it can lead to disposal of all advertising materials (30-100 million KRW, approx. $22,500-$75,000 in losses) or broadcast editing costs. This is especially frequent in the trot and variety show sectors, where there is a need to quickly verify individuals whose popularity suddenly surges.

Solution

Entering a talent's name automatically crawls news, communities, social media, and court precedents to provide a comprehensive report on past controversy history, current public sentiment, and legal risks. Real-time monitoring during the contract period sends immediate alerts when new issues arise, and calculates a risk rating (safe/caution/danger).

Target: Account executives at small advertising agencies with 5-30 employees, casting directors at broadcasting production companies, and brand marketing managers

Revenue Model: Per-transaction billing: 29,000 KRW (approx. $22) per verification report, monthly subscription of 99,000 KRW (approx. $74) per month (10 verifications + real-time monitoring for 3 people). Premium at 199,000 KRW (approx. $149) per month (unlimited verifications + monitoring for 10 people).

Ecosystem Role: Infrastructure

MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty

3.0/5

U Urgency

5.0/5

M Market

3.0/5

R Realizability

3.0/5

V Validation

3.0/5

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 (70%)

Tech Complexity

29.3/40

Data Availability

20.4/25

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 (60/100)

Competition

8.0/20

Market Demand

6.2/20

Timing

16.0/20

Revenue Signals

10.5/15

Pick-Axe Fit

12.0/15

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

Data Pipeline [medium] AI/ML [medium] Frontend [low]

Dashboard