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E-commerce, aviation, and Legal companies that have deployed AI chatbots need domain-specific training data (conversation scenarios) to improve bot performance, but in-house creation costs $1,500-3,000 (~200-400만원) per 100 scenarios and takes 2-3 weeks. Existing datasets are English-centric and don't fit Korean language and cultural context (honorifics, indirect complaint expressions, etc.), causing rework rates of 40% or more.
Domain-specific Korean conversation scenarios (E-commerce returns, flight delays, legal consultations, etc.) are crowdsourced, quality-reviewed, and sold on a Marketplace. Scenario writers (former CS agents, domain practitioners) use templates, and AI performs automated quality checks (naturalness, coverage, difficulty distribution).
| 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. |