B

AI Security Training Curriculum Designer

3.20

Derivation Chain

Step 1 Closing the AI security gap through hands-on training expansion
→
Step 2 Enterprise security team AI security upskilling
→
Step 3 Automated AI security training curriculum design with lab environments

Problem

Security managers (manager to senior manager level) at IT companies with 50-300 employees need to rapidly upskill their teams in AI security as global certifications like EC-Council expand, but designing Korean-language, practice-oriented training curricula takes 2-3 months. Outsourcing to external training providers costs $1,500-$3,750 per person.

Solution

Diagnoses team members' current security competency levels, then auto-generates curricula by combining Korean-language microlearning modules across topics such as OWASP Top 10 for LLM, AI supply chain security, and prompt injection defense. Each module includes hands-on scenarios (CTF-style), with a dashboard to track learning progress and competency growth.

Target: Security team leaders (manager to senior manager level) at IT companies with 50-300 employees, with annual training budgets of $7,500-$22,500
Revenue Model: B2B SaaS at $142/month per team (up to 10 members), plus $11/month per additional member. 2 months free with annual contract.
Ecosystem Role: Education
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
3.0/5
U Urgency
4.0/5
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.
SaaS N=.15 U=.20 M=.15 R=.30 V=.20 Senior N=.25 U=.25 M=.05 R=.30 V=.15

Feasibility (73%)

Tech Complexity
29.3/40
Data Availability
23.3/25
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 (56/100)

Competition
8.0/20
Market Demand
6.2/20
Timing
16.0/20
Revenue Signals
10.5/15
Pick-Axe Fit
10.5/15
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] Frontend [medium] AI/ML [low]
Dashboard