S

Research Grant Budget Automation Tool

4.05

Derivation Chain

Step 1 Expansion of National Research Foundation research grants
→
Step 2 Researcher burden of grant budget preparation
→
Step 3 Automated budget preparation and regulation validation service by grant type

Problem

University and research institute researchers (professors, senior researchers) applying for national R&D grants (e.g., National Research Foundation of Korea) must allocate budgets for personnel costs, research activity expenses, and indirect costs in compliance with funding regulations. Regulations differ by grant type (basic research, applied research, industry-academia collaboration) and change annually, requiring 8-15 hours per budget preparation, with approximately 30% rejection rate due to regulation violations.

Solution

(1) Auto-generate regulation-compliant budgets by entering grant type, duration, and number of participating researchers, (2) Automatically validate upper and lower limits per line item, (3) Alert and auto-revalidate existing budgets when regulations change. Core: Research funding regulation rule engine + grant type budget templates.

Target: University and government-funded research institute researchers (professors, PhD-level researchers), approximately 50,000 nationwide
Revenue Model: $22 per single grant budget preparation, $37/month subscription (unlimited). University group license $1,500/year.
Ecosystem Role: Infrastructure
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
3.0/5
U Urgency
5.0/5
M Market
4.0/5
R Realizability
4.0/5
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 (78%)

Tech Complexity
34.7/40
Data Availability
23.1/25
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 (59/100)

Competition
8.0/20
Market Demand
9.4/20
Timing
14.0/20
Revenue Signals
10.5/15
Pick-Axe Fit
10.5/15
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] Frontend [low] Data Pipeline [low]
Dashboard