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Procurement managers at small-to-mid server and module manufacturers (10-50 employees) purchasing DRAM need to manually aggregate price data from multiple sources like DRAMeXchange and JiChiMiNet to assess whether their current contract prices are fair relative to market spot prices, spending 3-5 hours per week. Delayed response of 1-2 weeks during spot price surges results in procurement cost differences of tens of thousands of dollars per transaction.
Automatically collects global DRAM spot price data and provides a product-specific (DDR5, HBM, LPDDR) price trend dashboard. Users input their contract prices to visualize their market position (upper/mid/lower tier), with Slack/KakaoTalk alerts sent during rapid price changes.
| 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. |