Agentic AI Permission Audit SaaS

2.85

Derivation Chain

Step 1 Galaxy Agentic AI

→

Step 2 Proliferation of autonomous AI agent actions

→

Step 3 Agent permission and behavior log audit service

Problem

With Samsung's Galaxy Unpacked 2026 announcing 'true Agentic AI,' smartphone AI agents can now autonomously perform actions like app installation, payments, and message sending. However, in enterprise BYOD environments, there is no way to track what permissions an employee's smartphone AI agent uses or what actions it takes. IT administrators spend an average of 3-5 days on manual log analysis when security incidents occur, and tracing personal data leak pathways is virtually impossible.

Solution

The service auto-collects AI agent permission requests and execution logs via MDM (Mobile Device Management) integration, visualizing anomalous behavior patterns (excessive payment attempts, unauthorized app access, etc.) on a real-time dashboard. It provides automatic alerts for policy violations and an API for temporarily suspending agent permissions, reducing enterprise security team response time by 90%.

Target: IT security officers and IT administrators at IT companies and fintech Startups with 50-500 employees

Revenue Model: SaaS Monthly Subscription at 2,900 won (~$2.20 USD) per device/month, 20% volume discount for 100+ devices, additional 15% discount for Annual Subscription

Ecosystem Role: Regulation

MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty

4.0/5

U Urgency

3.0/5

M Market

3.0/5

R Realizability

2.0/5

V Validation

3.0/5

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 (69%)

Tech Complexity

29.3/40

Data Availability

19.4/25

MVP Timeline

20.0/20

API Bonus

0.0/15

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 (55/100)

Competition

8.0/20

Market Demand

6.2/20

Timing

16.0/20

Revenue Signals

9.0/15

Pick-Axe Fit

10.5/15

Solo Buildability

5.0/10

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

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

Dashboard