A

Startup Grant MatchBot

4.20

Derivation Chain

Step 1 Graduate student startup support grants
→
Step 2 Cost of searching startup support programs
→
Step 3 Automated eligibility matching service for support programs

Problem

When graduate students and early-stage founders try to apply for government and municipal startup support programs (300+ annually), they must manually verify each posting's eligibility requirements, industry restrictions, regional conditions, and technology focus areas. On average, finding suitable grants takes 5-8 hours per week, document preparation takes 20-30 hours per application, and roughly 40% of applications are wasted on programs where the applicant doesn't meet the qualifications.

Solution

Users register their profile (education, technology domain, region, startup stage), and the system crawls 300+ support program postings in real time, ranking them by match rate. It auto-generates an eligibility checklist for each posting and customizes business plan templates to align with each program's evaluation criteria.

Target: STEM graduate students (ages 25-35) and pre-/early-stage founders in AI, Big Data, and Biotech
Revenue Model: Premium Subscription at KRW 29,000/month (~$22/mo) per user (match alerts + eligibility checks), Pro at KRW 79,000/month (~$59/mo) (includes AI business plan customization). Basic tier: 3 free matches/month.
Ecosystem Role: Supplier
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
2.0/5
U Urgency
5.0/5
M Market
4.0/5
R Realizability
5.0/5
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.
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 (74/100)

Competition
10.0/20
Market Demand
20.0/20
Timing
14.0/20
Revenue Signals
10.5/15
Pick-Axe Fit
12.0/15
Solo Buildability
7.0/10
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 [medium] AI/ML [medium] Frontend [low]
Dashboard