A
International Student Admin Onboarding Kit
3.80
Derivation Chain
Step 1
Expansion of dedicated international student programs at universities like Anyang and Woosong
→
Step 2
University administrative management of international students
→
Step 3
Self-service administrative onboarding tool for international students
Problem
As universities with dedicated international student programs rapidly increase, administrative tasks such as visa status changes, health insurance enrollment, bank account opening, and dormitory applications are being handled 1:1 by department offices. For every 100 international students, 2 full-time administrative staff are dedicated for 2–3 weeks at the start of each semester, with language barriers causing the same questions to be repeated.
Solution
Students input their nationality, visa type, and department to auto-generate a multilingual (Korean/English/Chinese/Vietnamese) checklist of required administrative procedures in order. Each step includes required documents, office locations (with maps), and reservation links, with progress shared to the university office via a dashboard.
NUMR-V Scores
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%)
Data Availability
23.1/25
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 (62/100)
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]
AI/ML [low]