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Public institutions that hire over 20,000 youth interns and contract workers annually under mandatory youth employment quotas require department-level onboarding managers to manually prepare OJT checklists, work manuals, mentor assignments, and evaluation forms for each cohort (2–4 times per year), spending an average of 4–6 hours per intern. When the person in charge changes, onboarding quality becomes inconsistent even within the same department.
A SaaS that auto-generates onboarding checklists, weekly OJT schedules, mentor matching suggestions, and mid-term/final evaluation forms when users input department name, role, and duration. It learns from previous cohort onboarding data to recommend department-specific content and tracks each intern's progress in real time.
| 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. |