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As AI adoption surges in biohealth, regulatory submissions for AI-based medical devices (SaMD) are flooding Korea's Ministry of Food and Drug Safety (MFDS). AI medical device regulatory documents (technical files, clinical trial protocols, performance test reports) must precisely follow MFDS AI medical device guidelines, requiring a dedicated Regulatory Affairs (RA) professional 3-6 months per submission. Small biotech firms struggle to even hire RA talent.
A SaaS where users select the AI medical device type (diagnostic aid, image analysis, prognosis prediction, etc.) and enter basic information, then auto-generates document templates aligned with MFDS AI medical device review guidelines, provides section-by-section writing guides with examples, and auto-checks for missing items.
| 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. |