B

AI Instructor Curriculum Certification Hub

2.70

Derivation Chain

Step 1 Mandatory AI Education for all public institution employees
→
Step 2 Surge in AI Education instructor demand
→
Step 3 AI instructor curriculum quality certification and public institution matching Platform

Problem

With mandatory AI Education across public institutions, demand for Freelancer AI instructors is surging, but there are no objective standards to verify instructor competency and curriculum quality. Institution managers rely solely on resumes and a single demo class to select instructors, and when training satisfaction is low, re-bidding takes an additional 3-4 weeks. Instructors also struggle to present their curricula in a standardized format.

Solution

When AI instructors upload their curricula, the Platform automatically performs coverage analysis against NIA/IITP Education standards, hands-on practice ratio checks, and difficulty-level suitability assessments to issue certification badges. Public institution managers can search instructors by certification score, specialty, and region, referencing historical training satisfaction data for matching.

Target: Freelancer AI Education instructors (2+ years experience), public institution Education program officers
Revenue Model: Instructor certification review at 39,000 KRW Per Transaction (~$29), public institution matching commission at 5% of contract value, Premium instructor profile at 19,000 KRW/month (~$14/month)
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
2.0/5
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 (70%)

Tech Complexity
29.3/40
Data Availability
20.8/25
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 (57/100)

Competition
8.0/20
Market Demand
9.4/20
Timing
16.0/20
Revenue Signals
7.5/15
Pick-Axe Fit
10.5/15
Solo Buildability
6.0/10
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