A
Export/Import HS Code Auto-Classifier
4.05
Derivation Chain
Step 1
Growth in Korean export/import trade activity
→
Step 2
Trade specialist customs workflow automation
→
Step 3
Automated HS code classification and tariff rate lookup tools
Problem
Trade specialists at SME export/import companies (annual revenue $3.75M–$37.5M) who handle customs without a licensed broker spend an average of 30–60 minutes per item classifying HS codes using the complex Korea Customs Service lookup system. Incorrect HS code classification results in penalties (2–5% of item value) and customs clearance delays (3–7 business days), with an average of 2–3 classification errors per year.
Solution
Users input product descriptions (Korean/English) and photos, and AI suggests 3–5 candidate HS codes with FTA tariff rates, requirement verification status, and similar rulings for each code. Includes auto-generation of Korea Customs Service advance classification ruling application drafts.
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 (56/100)
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
AI/ML [medium]
Backend [medium]
Frontend [low]