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K-Moonshot Grant MatchBot

3.20

Derivation Chain

Step 1 K-Moonshot Project (AI, biotech, semiconductor, quantum innovation acceleration)
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Step 2 Research institute & Startup grant participation demand
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Step 3 Automated grant announcement matching & proposal draft generation

Problem

The K-Moonshot Project is dramatically expanding government R&D grants in AI, biotech, semiconductors, and quantum fields, but leaders at small research institutes and Startups spend 2–3 hours per week checking multiple portals (NTIS, IRIS, etc.) for scattered grant announcements. Over 50% of eligible grants are missed due to manual cross-referencing of qualification criteria (tech domain, company size, region).

Solution

Aggregates R&D grant announcements from NTIS, IRIS, the Ministry of SMEs, and other sources, then auto-matches them against company profiles (tech domain, size, location, existing Patents) with a relevance score. Sends KakaoTalk alerts when a matching grant is found, and uses LLM to auto-draft proposal outlines and key sections, cutting application writing time by 50%.

Target: Startup founders and research institute grant managers in AI, biotech, and semiconductor fields (5–30 employees)
Revenue Model: SaaS Monthly Subscription at 59,000 KRW (~$44)/account (Free: 5 matching alerts/month, Premium: unlimited + proposal draft generation), 2 months free with Annual Subscription
Ecosystem Role: Education
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
3.0/5
U Urgency
3.0/5
M Market
3.0/5
R Realizability
3.0/5
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 (70%)

Tech Complexity
29.3/40
Data Availability
20.8/25
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 (58/100)

Competition
8.0/20
Market Demand
3.8/20
Timing
20.0/20
Revenue Signals
10.5/15
Pick-Axe Fit
10.5/15
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

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