A

AI-Driven Severance Maximization Planner

4.25

Derivation Chain

Step 1 AI-driven reduction in new hiring
→
Step 2 Increased voluntary resignation consideration among 40-50s middle managers due to AI replacement anxiety
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Step 3 Need to optimize severance, unemployment benefits, and pension amounts based on resignation timing and method

Problem

Office workers aged 45-55 facing department downsizing due to AI adoption cannot determine which path—recommended resignation, voluntary resignation, or early retirement—maximizes their combined severance pay, unemployment benefits, and pension. Labor consultant consultations cost 100,000-300,000 KRW (approx. $75-$225) per case, and online information only offers general guidance without calculations tailored to their tenure, salary, and pension enrollment history. A wrong choice can result in differences of millions to tens of millions of KRW (approx. $7,500-$75,000), yet most workers simply accept the company's proposed terms.

Solution

Users input their tenure, monthly salary, severance interim settlement history, National Pension enrollment period, and early retirement compensation conditions on the web. The service automatically calculates three scenarios—recommended resignation, voluntary resignation, and early retirement—showing (1) after-tax severance pay, (2) unemployment benefit eligibility, duration, and total amount, and (3) differences by National Pension withdrawal timing, then presents the optimal path in a comparison table. Differentiation: No existing service provides an integrated simulation of the legal and financial differences across resignation types.

Target: Office workers aged 45-55 at large and mid-sized enterprises, currently in departments subject to reorganization due to AI adoption, supporting a spouse and children, and considering career transition or early retirement after leaving.
Revenue Model: Basic 3-scenario comparison is free. PDF report with detailed tax calculations: 5,000 KRW (approx. $3.75) per report. Referral fee from labor consultant consultations.
Ecosystem Role: Supplier
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
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.
N=.15 U=.20 M=.15 R=.30 V=.20

Feasibility (68%)

Tech Complexity
29.3/40
Data Availability
18.3/25
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 (74/100)

Competition
10.0/20
Market Demand
20.0/20
Timing
16.0/20
Revenue Signals
10.5/15
Pick-Axe Fit
10.5/15
Solo Buildability
7.0/10
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

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