GovAI Metrics – AI Administration Performance Measurement Tool

3.20

Derivation Chain

Step 1 Expansion of municipal AI administration adoption

→

Step 2 Increase in AI administration Solution vendors

→

Step 3 Tools for objectively measuring Solution performance

Problem

As more municipalities adopt AI administration systems (like Seoul's Mapo District), there is no systematic framework to quantitatively measure actual outcomes (false positive rates, response time reduction, budget savings) after deploying AI systems for crowd prediction, flood forecasting, etc. Solution vendors spend 40–60 hours manually writing performance reports 2–3 times per year, and additional effort is required when municipal auditors demand quantitative evidence.

Solution

Automatically collects prediction logs, alert histories, and actual incident data from AI administration systems, then visualizes accuracy, precision, response time reduction rates, and estimated budget savings on a real-time dashboard. Quarterly performance Report PDFs are auto-generated with format support aligned to Ministry of the Interior and Safety performance indicator templates.

Target: AI administration Solution vendors (IT companies with 5–30 employees) and municipal smart city departments

Revenue Model: SaaS Monthly Subscription $367.50/municipal project, $292.50/month for Annual Subscription, custom Report format $75 Per Transaction additional

Ecosystem Role: Infrastructure

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 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 (68%)

Tech Complexity

29.3/40

Data Availability

18.3/25

MVP Timeline

20.0/20

API Bonus

0.0/15

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 (59/100)

Competition

8.0/20

Market Demand

9.4/20

Timing

16.0/20

Revenue Signals

10.5/15

Pick-Axe Fit

10.5/15

Solo Buildability

5.0/10

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] Data Pipeline [low]

Dashboard