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Tech industry job seekers and VC/PE investment analysts track global layoff trends by checking 10+ sources daily — Twitter, Blind, layoffs.fyi, news outlets, etc. Korean company restructuring information rarely appears on English-language sites, and extracting structured data (company name, scale, affected departments) from domestic news is difficult, consuming 3–5 hours per week on information gathering.
Automatically collects global and domestic layoff news, normalizing it into structured data fields: company name, layoff scale, affected departments, and timing. Offers filtering by industry and company size, watchlist alerts for companies of interest, and weekly trend report emails.
| 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. |