S
Tech Startup Permit & Grant Auto-Matcher
4.15
Derivation Chain
Step 1
AI proliferation drives tech startups to all-time highs
→
Step 2
Administrative support services for tech founders
→
Step 3
Industry-specific permit + grant auto-matching SaaS
Problem
As tech-based startups hit record highs with a surge in new ICT and AI companies, early-stage founders spend an average of 2-3 weeks and $375-$1,125 (~50-150 million KRW) on administrative agents to identify the permits required for their business model (online retail license, personal data processing, AI impact assessment, etc.) and match eligible government grants (TIPS, Startup Leap Package, and 50+ others). Cases of post-launch fines due to missed permits are also common.
Solution
(1) Enter your business registration industry code and service keywords to auto-generate a list of required and optional permits. (2) Match the top 10 eligible government grants based on qualification criteria and provide deadline alerts. (3) Deliver permit application templates and step-by-step procedural guides. Eliminates permit omission risk at 1/5 the cost of an administrative agent.
NUMR-V Scores
NUMR-V Scoring System
| 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. |
SaaS N=.15 U=.20 M=.15 R=.30 V=.20
Senior N=.25 U=.25 M=.05 R=.30 V=.15
Feasibility (70%)
Data Availability
20.8/25
Feasibility Breakdown
| 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. |
Market Validation (57/100)
Validation Breakdown
| 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. |
Technical Requirements
Backend [medium]
Frontend [low]
Data Pipeline [medium]