B

AI Cost Allocation & Settlement

4.20

Derivation Chain

Step 1 OpenAI's $110B investment — surge in AI API usage
→
Step 2 Rapid increase in corporate AI API costs
→
Step 3 Service that allocates and settles AI API costs by department/project

Problem

In SMEs (20-200 employees) using AI APIs (OpenAI, Claude, Naver Clova, etc.) across multiple departments, the monthly bill comes to a consolidated account, making it impossible to attribute costs by department or project. The finance team spends 3-5 days each month on manual reconciliation, and only discovers overspending departments after the fact, leaving monthly waste of hundreds of thousands to millions of KRW (approx. $75 to $6,750) unaddressed.

Solution

(1) Wrap existing AI API keys with a proxy to aggregate usage and costs in real time by department/project tag, (2) set budget limits per department and send Slack/email alerts when exceeded, (3) automatically generate monthly settlement reports by department and deliver them to management and finance teams.

Target: Finance teams or CTOs at IT companies and startups with 20-200 employees, companies spending over 1 million KRW (approx. $750) per month on AI API costs.
Revenue Model: SaaS monthly subscription — Starter: 59,000 KRW/month (approx. $44) for 5 API keys, Growth: 149,000 KRW/month (approx. $112) for 20 API keys + Slack integration, 20% discount for annual billing.
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 (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 (61/100)

Competition
8.0/20
Market Demand
6.2/20
Timing
16.0/20
Revenue Signals
12.0/15
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 [medium]
Dashboard