B
Shadow AI Usage Detection Dashboard
3.40
Derivation Chain
Step 1
AI democratization drives rapid growth in voluntary employee AI tool usage
→
Step 2
CIO lack of Shadow AI visibility
→
Step 3
Infrastructure for enterprise AI governance policy tools
→
Step 4
Network-level Shadow AI usage detection and classification tool
Problem
Even when enterprises establish AI governance policies, enforcement is impossible without visibility into which AI tools employees are using and how much. IT teams at companies with 50–300 employees cannot track usage of 200+ AI SaaS products like ChatGPT, Claude, Copilot, and Midjourney, and confidential data leaks to external AI tools average 3–5 incidents per quarter.
Solution
Detects and classifies employee AI tool access patterns via corporate proxy/DNS logs or browser extensions, and visualizes approved vs. unapproved AI usage on a dashboard. Provides real-time alerts for data leak risk behaviors (file uploads, code pasting) and auto-generates usage reports by department and role.
NUMR-V Scores
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 (62%)
Data Availability
17.5/25
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 (63/100)
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]
Infrastructure [medium]