B

AI Model Government Procurement Test Report Generator

3.35

Derivation Chain

Step 1 National Growth Fund AI semiconductor investment
→
Step 2 Expansion of AI solution government procurement
→
Step 3 Increasing demand for AI model performance test reports
→
Step 4 Automated test report generation tool

Problem

As government AI procurement expands, submitting AI model performance test reports (accuracy, bias, security, etc.) has become mandatory. However, the AI Basic Act requires 20+ test items, each with different measurement methodologies, so it takes SME AI companies 2-3 weeks to prepare a single test report, or $3,750-$7,500 (~5-10 million KRW) when outsourced. Missing test items or measurement errors risk procurement rejection.

Solution

Connect an AI model with test datasets to automatically run performance, bias, and security tests compliant with the AI Basic Act and government procurement standards, generating standardized test reports in PDF format. Built-in test item checklists and measurement methodology guides prevent omissions.

Target: ML engineers and QA managers at AI Startups with 5-30 employees supplying AI solutions to government projects
Revenue Model: Per Transaction: $217 (~290,000 KRW) per test report, Monthly Subscription: $367 (~490,000 KRW) (includes 3 reports/month + unlimited retests)
Ecosystem Role: Regulation
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
4.0/5
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
20.6/25
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 (66/100)

Competition
8.0/20
Market Demand
9.4/20
Timing
18.0/20
Revenue Signals
12.0/15
Pick-Axe Fit
13.5/15
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

Backend [medium] AI/ML [medium] Frontend [low]
Dashboard