B

OpenAI Cost Department Allocation Engine

4.20

Derivation Chain

Step 1 OpenAI raises 159 trillion KRW investment and expands AI infrastructure (approx. $119.25 billion)
→
Step 2 Surge in enterprise AI API usage
→
Step 3 Allocation and settlement of AI API costs by department and project

Problem

In IT companies with 20-200 employees, when using multiple AI APIs such as OpenAI and Claude, integrated billing under one organization account makes it impossible to allocate costs by department or project based on actual usage. The finance team spends 3-5 days on manual Excel reconciliation at month-end, and unclear allocation criteria cause an average of 2-3 inter-departmental disputes per quarter.

Solution

Collects usage logs from major AI APIs (OpenAI, Anthropic, Google, etc.) via API key or proxy gateway, and visualizes token usage and costs by department, project, and individual on a real-time dashboard. Provides automatic month-end settlement report generation, budget overrun alerts, and Slack-integrated cost notifications.

Target: Finance team leads and CTOs at IT service companies with 20-200 employees, and mid-sized agencies that have adopted AI in their operations.
Revenue Model: SaaS monthly subscription: 59,000 KRW per month for 50 seats (approx. $44.25), additional seats at 800 KRW per month each (approx. $0.60). 15% discount for annual payment.
Ecosystem Role: Infrastructure
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
2.0/5
U Urgency
5.0/5
M Market
4.0/5
R Realizability
5.0/5
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.
N=.15 U=.20 M=.15 R=.30 V=.20

Feasibility (74%)

Tech Complexity
34.7/40
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 (76/100)

Competition
10.0/20
Market Demand
20.0/20
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 [low] Infrastructure [low]
Dashboard