S

Sensitive Data Classification Pre-Screening

4.40

Derivation Chain

Step 1 Policy for transferring sensitive public data to private cloud
→
Step 2 Demand for sensitivity classification of data to be transferred
→
Step 3 Automatic pre-screening tool for dataset sensitivity levels

Competitor references

Problem

As public data moves to private cloud, information security officers at each institution must manually classify thousands of datasets into sensitivity levels (general/restricted/secret). Each dataset takes 30 minutes to 1 hour, and interpretation varies by officer, leading to audit risk.

Solution

Upload dataset metadata (column names, sample data), and automatically determine sensitivity level based on the Personal Information Protection Act and Public Data Act. Provide the basis for determination (relevant legal provisions, matched sensitive patterns) for audit evidence.

Target: Information security officers (grade 5-7) at central government ministries and local governments, public institution cloud migration PMs, and cloud migration consulting firms (10-30 employees).
Revenue Model: API pay-as-you-go: 5,000 KRW per dataset (up to 100) (approx. $3.75), 3,000 KRW per dataset for 101+ (approx. $2.25). Annual flat rate for institutions: 5,000,000 KRW (approx. $3,750) for unlimited.
Ecosystem Role: Regulation
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
4.0/5
U Urgency
5.0/5
M Market
4.0/5
R Realizability
4.0/5
V Validation
5.0/5
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
20.6/25
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 (80/100)

Competition
10.0/20
Market Demand
20.0/20
Timing
20.0/20
Revenue Signals
10.5/15
Pick-Axe Fit
15.0/15
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] Frontend [low] AI/ML [medium]
Dashboard