B

AI Policy Impact Alerts for My Company

3.25

Derivation Chain

Step 1 News of the establishment of an AI Policy Office under the Ministry of Gender Equality and Family
→
Step 2 Impact of government AI policies and regulatory changes on businesses
→
Step 3 Middle managers in their 50s cannot identify which AI regulations apply to their departments
→
Step 4 Customized AI policy change monitoring by department and industry

Problem

Middle managers in their 50s (team leaders and department heads) face a flood of government AI-related policies, but it's hard to determine which ones actually affect their departments (HR, marketing, production, legal). The AI Framework Act, amendments to the Personal Information Protection Act, and industry-specific AI guidelines are announced at different times by different ministries, and tracking the official gazette, press releases, and legal information takes 2-3 hours per week. As a result, regulatory responses are delayed, leading to audit findings or unnecessary overreactions that delay projects.

Solution

Set your industry (manufacturing, finance, medical, education, etc.) and department (HR, marketing, IT, legal) on the web, and it automatically collects AI-related changes from government ministry press releases, legislative notices, and guidelines, providing a weekly briefing with a 'relevant/not relevant to our department' determination. It includes a 'required action checklist' for each policy and a D-day alert for the effective date.

Target: Aged 50-58, middle managers (team leaders, department heads) at companies with 300+ employees, driving AI adoption or responsible for AI-related regulatory response.
Revenue Model: Free for individuals (weekly email briefing). Team-level dashboard + checklist management + legal consultation connection, B2B SaaS at 50,000 KRW/month per team (approx. $37.50).
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
3.0/5
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.
N=.15 U=.20 M=.15 R=.30 V=.20

Feasibility (70%)

Tech Complexity
29.3/40
Data Availability
20.4/25
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 (62/100)

Competition
8.0/20
Market Demand
6.2/20
Timing
20.0/20
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

Data Pipeline [medium] Backend [medium] Frontend [low]
Dashboard