B
Festival Submission Auto-Judge
3.15
Derivation Chain
Step 1
Public data utilization island expo
→
Step 2
Competition judging process
→
Step 3
Automated submission evaluation and comparison SaaS for judges
Problem
When local government competition judges (5-10 people) manually evaluate 30-100 submissions, score discrepancies arise from differing interpretations of judging criteria, and the review process takes 2-3 days. When transparency issues trigger appeals, additional administrative costs of 500,000-1,000,000 KRW (~$375-$750) per case are incurred.
Solution
Automatically performs first-round evaluation of submissions using structured rubrics for data utilization, completeness, and creativity, while visualizing score variance among judges in real time. When appeals are filed, an audit trail report with scoring rationale is automatically generated.
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 (74%)
Data Availability
24.4/25
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 (57/100)
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]
AI/ML [medium]
Frontend [low]