B

Subsidy Eligibility Pre-Screener

3.50

Derivation Chain

Step 1 Livelihood subsidy policy expansion
→
Step 2 Subsidy application brokerage by municipality
→
Step 3 Automated pre-screening of subsidy eligibility before application

Problem

Small Business Owners with annual revenue under ~$225,000 and Freelancers trying to compare eligibility requirements across livelihood subsidies and small business support programs announced separately by central government, metropolitan, and municipal authorities spend an average of 3-5 hours per application. Misinterpreting requirements leads to ineligible applications or missed eligible subsidies in roughly 20-30% of all applicants. This results in losing ~$375-$2,250 in annual subsidies per person, or wasting an additional 2-3 hours on resubmission after rejection.

Solution

A SaaS that auto-matches currently available subsidies when users input their business registration number, income information, and region, and predicts eligibility probability for each subsidy. (1) Crawls public data portal subsidy announcements + LLM-based structured parsing of eligibility requirements, (2) Automatic eligibility determination against user profile, (3) Application document checklist and deadline alerts.

Target: Small Business Owners with annual revenue ~$75,000-$375,000 and Freelancer business operators (ages 30-50s)
Revenue Model: Premium SaaS Monthly Subscription ~$22/month per account. Free Plan: 3 lookups/month. Paid Plan: unlimited lookups + alerts + document checklist. 20% discount for Annual Subscription.
Ecosystem Role: Infrastructure
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
2.0/5
U Urgency
4.0/5
M Market
4.0/5
R Realizability
4.0/5
V Validation
3.0/5
NUMR-V Scoring System
N Novelty1-5How uncommon the service is in market context.
U Urgency1-5How urgently users need this problem solved now.
M Market1-5Market size and growth potential from proxy indicators.
R Realizability1-5Buildability for a small team with realistic constraints.
V Validation1-5Validation signal quality from competition and demand data.
Each dimension is scored 1-5 and weighted into grade S/A/B/C/D.
SaaS N=.15 U=.20 M=.15 R=.30 V=.20 Senior N=.25 U=.25 M=.05 R=.30 V=.15

Feasibility (68%)

Tech Complexity
29.3/40
Data Availability
18.8/25
MVP Timeline
20.0/20
API Bonus
0.0/15
Feasibility Breakdown
Tech Complexity/ 40Difficulty of core implementation stack.
Data Availability/ 25Practical availability and cost of required data.
MVP Timeline/ 20Expected time to ship a usable MVP.
API Bonus/ 15Bonus for viable public API leverage.
Total 100 points; below 50% is filtered out.

Market Validation (56/100)

Competition
8.0/20
Market Demand
6.2/20
Timing
16.0/20
Revenue Signals
10.5/15
Pick-Axe Fit
10.5/15
Solo Buildability
5.0/10
Validation Breakdown
Competition/ 20Signal quality from competitor landscape.
Market Demand/ 20Demand proxies from search and mention patterns.
Timing/ 20Fit with current shifts in tech, behavior, and regulation.
Revenue Signals/ 15Reference evidence for monetization viability.
Pick-Axe Fit/ 15How well the concept serves participants in a trend.
Solo Buildability/ 10Practicality for lean-team implementation.
Total 100 points; below 50 is filtered out.

Technical Requirements

Backend [medium] AI/ML [medium] Frontend [low]
Dashboard