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A 57-year-old early retiree needs to combine National Pension (with choice of start date), retirement pension (lump sum vs. annuity), personal pension, part-time earned income, and financial income to secure 3.5 million KRW (~$2,625) per month for living expenses. Since each income source has different tax brackets and health insurance premium calculation criteria, changing the combination can result in a difference of 500,000-800,000 KRW (~$375-600) per month in after-tax take-home pay. Currently, the only way to optimize this combination is through a paid financial planner (300,000-500,000 KRW (~$225-375) per session), and doing it yourself requires visiting three websites (National Pension Service, National Tax Service, and National Health Insurance Service) and takes 5-6 hours.
On the web, (1) input expected pension amount, severance pay, financial assets, and desired earned income, then (2) automatically calculate monthly after-tax take-home pay and health insurance premiums for scenarios such as age 60, 62, and 65, and (3) present the top 3 optimal combinations in a comparison table. A realistic simulation that reflects National Pension start date, retirement pension payout method, and separate taxation criteria for financial income.
| N Novelty | 1-5 | How uncommon the service is in market context. |
| U Urgency | 1-5 | How urgently users need this problem solved now. |
| M Market | 1-5 | Market size and growth potential from proxy indicators. |
| R Realizability | 1-5 | Buildability for a small team with realistic constraints. |
| V Validation | 1-5 | Validation signal quality from competition and demand data. |
| Tech Complexity | / 40 | Difficulty of core implementation stack. |
| Data Availability | / 25 | Practical availability and cost of required data. |
| MVP Timeline | / 20 | Expected time to ship a usable MVP. |
| API Bonus | / 15 | Bonus for viable public API leverage. |
| Competition | / 20 | Signal quality from competitor landscape. |
| Market Demand | / 20 | Demand proxies from search and mention patterns. |
| Timing | / 20 | Fit with current shifts in tech, behavior, and regulation. |
| Revenue Signals | / 15 | Reference evidence for monetization viability. |
| Pick-Axe Fit | / 15 | How well the concept serves participants in a trend. |
| Solo Buildability | / 10 | Practicality for lean-team implementation. |