A

TOPIK Exam Practice Coach for International Students

3.75

Derivation Chain

Step 1 International student education cooperation MOU & Korean language curriculum
→
Step 2 Need for international students to improve Korean proficiency
→
Step 3 TOPIK exam preparation market
→
Step 4 Personalized TOPIK study coaching SaaS

Problem

Approximately 400,000 international students per year need TOPIK Level 4+ for Korean university admission or employment, but existing study apps offer only basic quizzes with no scoring or feedback for the writing section. Private 1:1 tutoring costs ₩40,000–60,000/hour (~$30–45), and there is a lack of personalized feedback addressing native-language-specific weaknesses (e.g., Chinese speakers confusing Sino-Korean words, Vietnamese speakers struggling with final consonants).

Solution

Provides AI-powered mock exams across listening, reading, and writing sections based on past TOPIK questions. The writing section features LLM-based instant scoring against official criteria (content, structure, language use) with correction suggestions. Analyzes the learner's native language and error patterns to auto-generate a weakness-focused study curriculum, plus weekly progress reports.

Target: International students and workers aged 20–30 preparing for TOPIK Levels 3–6, particularly D-2 (student) and E-9 (worker) visa holders
Revenue Model: SaaS Monthly Subscription: ₩9,900/month (~$7.50) per account (all sections), writing correction only at ₩1,900 (~$1.40) Per Transaction, 30% discount for Annual Subscription
Ecosystem Role: Education
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
3.0/5
U Urgency
3.0/5
M Market
4.0/5
R Realizability
5.0/5
V Validation
3.0/5
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.
SaaS N=.15 U=.20 M=.15 R=.30 V=.20 Senior N=.25 U=.25 M=.05 R=.30 V=.15

Feasibility (73%)

Tech Complexity
29.3/40
Data Availability
23.3/25
MVP Timeline
20.0/20
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 (53/100)

Competition
8.0/20
Market Demand
6.2/20
Timing
14.0/20
Revenue Signals
10.5/15
Pick-Axe Fit
9.0/15
Solo Buildability
5.0/10
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

AI/ML [medium] Backend [medium] Frontend [low]
Dashboard