Agent Swarm Billing Forecaster

4.35

Derivation Chain

Step 1 AI multi-agent framework proliferation

→

Step 2 Agent operational cost management demand

→

Step 3 Per-agent-call Billing prediction and optimization tool

Problem

Teams running multi-agent systems (such as Agent Swarm) in production face unpredictably skyrocketing LLM API costs due to recursive inter-agent calls. A single user request can internally trigger dozens to hundreds of LLM calls, but there is no way to break down which agent consumed how much—cost overruns are only discovered on the end-of-month invoice.

Solution

Inserts a lightweight proxy into the agent orchestrator to track LLM call count, tokens, and cost per agent and per task in real time, providing budget overrun forecast alerts plus caching/batching recommendations for cost optimization.

Target: AI Startups with 5-50 staff operating multi-agent systems, SaaS company backend teams

Revenue Model: SaaS Monthly Subscription: Free (up to 10,000 calls/month tracked), Pro at 59,000 KRW (~$44)/month (500,000 calls/month), Enterprise at 199,000 KRW (~$149)/month (unlimited + custom alerts)

Ecosystem Role: Infrastructure

MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty

5.0/5

U Urgency

5.0/5

M Market

4.0/5

R Realizability

4.0/5

V Validation

4.0/5

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 (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	/ 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 (60/100)

Competition

8.0/20

Market Demand

6.2/20

Timing

18.0/20

Revenue Signals

10.5/15

Pick-Axe Fit

12.0/15

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 [low] Infrastructure [low]

Dashboard