Regional University Joint Credit Matching Board

3.00

Derivation Chain

Step 1 Kongju National / regional university mega-regional cooperation

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Step 2 Demand for joint inter-university curriculum operations

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Step 3 Credit exchange course matching and completion management Platform

Problem

Administrative teams at regional national universities pursuing mega-regional cooperation (e.g., Pusan National-Jeju National, Kongju National) manually match credit exchange courses, spending an average of 30 minutes per course comparing curricula across 200+ courses annually—over 100 hours total. 40% of students give up on exchange courses because they cannot find available course information.

Solution

Automatically crawls partner university curricula to match course similarity (based on syllabi), recommends personalized exchange courses for students, and generates automatic credit mapping Reports. Provides separate approval workflows for admin teams and a discovery UI for students.

Target: Registrar/academic affairs staff at regional national universities with 5,000+ enrolled students

Revenue Model: Per-university Annual Subscription license at 500,000 KRW (~$375)/month per university; 30% discount for simultaneous contracts with 3+ partner universities

Ecosystem Role: Infrastructure

MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty

2.0/5

U Urgency

3.0/5

M Market

2.0/5

R Realizability

4.0/5

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.

SaaS N=.15 U=.20 M=.15 R=.30 V=.20 Senior N=.25 U=.25 M=.05 R=.30 V=.15

Feasibility (72%)

Tech Complexity

29.3/40

Data Availability

23.1/25

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 (53/100)

Competition

8.0/20

Market Demand

6.2/20

Timing

14.0/20

Revenue Signals

7.5/15

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] Data Pipeline [low]

Dashboard