B

Comment Quality Score API

3.10

Derivation Chain

Step 1 Respectify comment-educational moderator
→
Step 2 Community moderation tool ecosystem
→
Step 3 Quality measurement Infrastructure for moderation SaaS

Problem

Korean online community and media Platform operators have built profanity-level moderation but cannot identify low-quality comments that don't technically violate rules — such as 'emotionally charged comments with no logical rebuttal' or 'polite comments containing misinformation.' This degrades comment section quality and drives advertiser attrition (comment quality correlates with ad CPM by 15–20% on average). Building a proprietary quality model requires 3–6 months and ML engineer hires.

Solution

(1) A REST API that scores comment text (0–100) across 4 axes: logical coherence, constructiveness, factual grounding, and emotional intensity; (2) Platform operators can set score thresholds for auto-hide/highlight actions; (3) automated weekly community health Report generation. Enables instant comment quality management without an in-house ML team.

Target: Service operations and development teams at Korean community Platforms, news media, and vertical commerce sites with MAU of 10K–500K
Revenue Model: API usage-based Billing at 5 KRW (~$0.004) Per Transaction (billed in 1,000-unit blocks). Monthly minimum 50,000 KRW (~$37.50). Volume discount to 3 KRW (~$0.002) Per Transaction above 1M monthly calls. Dashboard Report add-on at 99,000 KRW (~$74)/month
Ecosystem Role: Infrastructure
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
4.0/5
U Urgency
2.0/5
M Market
2.0/5
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 (73%)

Tech Complexity
29.3/40
Data Availability
23.3/25
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 (51/100)

Competition
8.0/20
Market Demand
6.2/20
Timing
14.0/20
Revenue Signals
9.0/15
Pick-Axe Fit
9.0/15
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

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