B

AI Talent Salary Benchmark

3.00

Derivation Chain

Step 1 Intensifying AI talent recruitment wars
→
Step 2 Surging AI talent salaries and compensation
→
Step 3 Market salary benchmarking service for AI talent recruitment

Problem

As the global AI talent war intensifies — with OpenAI recruiting Meta's AI lead, for example — HR teams at mid-sized domestic IT companies (especially those with 50-300 employees) cannot determine appropriate salary, stock option, and signing bonus levels for AI roles (ML engineers, prompt engineers, AI PMs, etc.). This frequently results in rejected offers or overpaying by 20-30% above market rate.

Solution

Anonymously crawls AI job compensation data from Blind, Jobplanet, Wanted, and LinkedIn, then provides real-time dashboards showing salary distributions (25th/50th/75th/90th percentile) by title, experience, tech stack, and company size. When a specific position offer amount is entered, it automatically rates market competitiveness (High/Medium/Low).

Target: HR team leads and recruiters at AI/IT companies with 50-300 employees, hiring 5+ AI positions annually
Revenue Model: SaaS Monthly Subscription at 199,000 won (~$149)/company (up to 5 seats), additional seats at 30,000 won (~$22.50)/month, 20% discount for annual billing
Ecosystem Role: Infrastructure
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
2.0/5
U Urgency
3.0/5
M Market
4.0/5
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 (66%)

Tech Complexity
24.0/40
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 (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

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