A

AI Recruitment JD Auto-Builder

4.00

Derivation Chain

Step 1 68.5% of companies planning to hire AI talent
→
Step 2 Writing AI talent recruitment postings
→
Step 3 AI job description standardization tool

Problem

HR managers at SMEs (50-200 employees) trying to hire AI talent struggle to write AI/ML job descriptions (JDs) — they don't know the appropriate level of tech stack requirements, end up copy-pasting from other companies' postings or listing excessive requirements, causing qualified candidates to drop off. Writing a single JD takes an average of 3-4 hours, and filtering unqualified applicants wastes an additional 6 hours per week.

Solution

(1) Input job level (Junior/Mid/Senior) and project type to auto-generate a market-standard JD draft, (2) provide a requirements appropriateness score benchmarked against similar companies' postings, (3) generate a predicted attractiveness score from the applicant's perspective. One-click export in formats compatible with major Korean recruitment platforms (Saramin, Wanted).

Target: HR managers and recruitment leads at non-IT SMEs with 50-200 employees
Revenue Model: Premium SaaS at 29,000 KRW (~$22)/month per account (10 JDs/month), additional JDs at 3,000 KRW (~$2.25) each. 15% discount for annual Subscription.
Ecosystem Role: Infrastructure
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
2.0/5
U Urgency
4.0/5
M Market
4.0/5
R Realizability
5.0/5
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 (72%)

Tech Complexity
29.3/40
Data Availability
22.5/25
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 (59/100)

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
8.0/10
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 [low] Data Pipeline [medium]
Dashboard