B

AI Coding Cost Settlement Dashboard

3.65

Derivation Chain

Step 1 Growing awareness of AI coding tool costs
→
Step 2 Monitoring AI coding tool usage
→
Step 3 Automatic allocation and settlement of AI coding costs by department and project

Problem

IT agencies and startups subscribe to AI coding tools like GitHub Copilot, Claude Code, and Cursor on a team basis, incurring monthly costs of 1 to 5 million KRW (approx. $750 to $3,750), but it is impossible to track how much each project or department actually uses. The finance team cannot allocate AI tool costs by project, distorting profitability analysis, and development team leads cannot identify heavy users, leaving no basis for license optimization.

Solution

Collect usage logs from each AI coding tool (API call count, token usage, session time) to automatically allocate costs by project, department, and individual, and generate monthly settlement reports. Provide unused license detection, cost anomaly alerts, and a dashboard estimating project-level ROI (code productivity vs. AI tool cost).

Target: CTOs or development team leads at IT agencies and startups with 10-100 employees
Revenue Model: SaaS monthly subscription: 39,000 KRW/month per team (approx. $29) including 10 seats, additional seats at 3,000 KRW/month (approx. $2.25) each. 15% discount for annual billing.
Ecosystem Role: Supplier
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
4.0/5
U Urgency
4.0/5
M Market
3.0/5
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.
N=.15 U=.20 M=.15 R=.30 V=.20

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/ 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 (60/100)

Competition
8.0/20
Market Demand
6.2/20
Timing
16.0/20
Revenue Signals
10.5/15
Pick-Axe Fit
12.0/15
Solo Buildability
7.0/10
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] Frontend [medium] Infrastructure [low]
Dashboard