A

AI Chatbot Safety Filter Benchmarker

4.05

Derivation Chain

Step 1 AI misuse crime cases (e.g., ChatGPT queries for harmful methods)
→
Step 2 Need to strengthen AI service safety filters
→
Step 3 Safety filter quality benchmark and testing SaaS for AI service operators

Problem

Startups operating AI chatbot and LLM services lack systematic methods to test the effectiveness of their safety filters (harmful query blocking, dangerous content generation prevention). As AI-related crime cases gain media attention and regulatory pressure mounts, safety filter testing is still done manually, with an average 2–3 week delay in responding to new bypass techniques.

Solution

Automated benchmarking of AI service safety filters using industry-standard harmful prompt test sets (Korean-language specialized). Provides category-specific blocking rate reports (violence, drugs, financial fraud, personal data), bypass technique detection, and competitive safety level comparisons.

Target: Safety/Trust teams at AI chatbot and LLM service startups (teams of 2–5), CTOs and PMs, aged 25–40
Revenue Model: SaaS Monthly Subscription at ~$74/service (~99,000 KRW, includes 1,000 tests/month), additional 1,000 tests at ~$29 (~39,000 KRW). Enterprise plan at ~$224/month (~299,000 KRW, unlimited).
Ecosystem Role: Regulation
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
3.0/5
U Urgency
5.0/5
M Market
4.0/5
R Realizability
4.0/5
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 (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 (65/100)

Competition
8.0/20
Market Demand
6.2/20
Timing
20.0/20
Revenue Signals
10.5/15
Pick-Axe Fit
15.0/15
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

Backend [medium] Data Pipeline [medium] Frontend [low]
Dashboard