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AI Disinformation Detection Reporter

3.55

Derivation Chain

Step 1 Proliferation of AI-Powered Foreign Disinformation Operations
→
Step 2 Demand for AI-Generated Disinformation Detection
→
Step 3 Enterprise/institutional AI disinformation monitoring report for brand protection

Problem

Domestic companies and public institutions face increasing cases where AI-generated disinformation (deepfakes, bot-driven opinion manipulation) from overseas damages brand reputation and stock prices. They lack the multilingual processing and AI-generated content detection capabilities needed to monitor global social media and news independently, while external consulting costs $3,750-15,000 per engagement. In most cases, organizations only become aware of disinformation campaigns after they have already spread, missing the critical 24-hour response window.

Solution

Users register their brand/person keywords, and the system crawls global social media, news, and forums to automatically detect suspected AI-generated content and sends daily reports. Core features: (1) multilingual (Korean/English/Chinese/Japanese) AI-generated content probability scoring, (2) spread pathway visualization and bot network clustering, (3) automated alerts by crisis severity level with initial response templates.

Target: PR/IR managers at mid-sized companies (revenue $7.5M-375M) and local government PR teams
Revenue Model: SaaS monthly subscription at $367/brand (10 keywords), additional keywords at $22.50/month each, urgent analysis report at $225 per transaction
Ecosystem Role: Supplier
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
3.0/5
U Urgency
4.0/5
M Market
4.0/5
R Realizability
3.0/5
V Validation
4.0/5
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 (69%)

Tech Complexity
29.3/40
Data Availability
19.6/25
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 (62/100)

Competition
10.0/20
Market Demand
20.0/20
Timing
14.0/20
Revenue Signals
7.5/15
Pick-Axe Fit
7.5/15
Solo Buildability
3.0/10
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