Units360.ai — AI Spend Management Demo

Units360.ai

Watch how Acme Gaming manages AI credit quotas across LLM and VR services — from setup to auto-generated usage report — with zero engineering overhead.

🎮 Industry Use Case: AI Spend Management · Enterprise

Define Quota

→

Consume

→

Alert

→

Enforce

→

Report

💡 Commentary

▸Acme Gaming is an example of an organisation that uses two AI services — an LLM assistant and a VR video generator.
▸Every LLM token and every video minute converts into AI credits — a single internal quota currency.
▸The quota is enforced at the credit level, across every backend service.

⚠

80% of credit quota used — employee notified

AI Credit Usage

/ 1,000 AI credit quota 0%

LLM (GPT-4)

0 cr

0 tokens @ 200:1

VR Video Gen

0 cr

0 min @ 5:1

ACT 1 OF 5

Set Up Credit Quota

Acme Gaming · AI Tools Budget

Acme Gaming assigns each team member 1,000 AI credits per month. Credits cover two services: the LLM assistant (200 tokens = 1 credit) and the VR video generator (5 video minutes = 1 credit).

AI Spend Monitor

LLM (GPT-4)

0 tokens

0 cr

VR Video Gen

0 min

0 cr

Total AI Credits 0 / 1,000 cr

00:00:00 units360 credit quota engine initializing...

✓

AI Credit Usage Report

EmployeeJordan Chen

PeriodMay 2026

LLM (GPT-4)520 credits

104,000 tokens @ 200:1

VR Video Gen480 credits

2,400 min @ 5:1

Total Used1,000 / 1,000 cr

Speed:

What is Units360? Acme Gaming Conversions Unit Account Transaction Config CloudEvents

Platform Overview

🚀 What is Units360?

Units360.ai is a low-code usage metering platform — the operating system for any business that manages services by the unit. Instead of building custom metering infrastructure, you define your unit model once, and Units360 auto-provisions everything else.

In this demo, the internal unit is AI credit — a company-defined quota currency that covers multiple backend services (LLM + VR video generation). But Units360 works equally for kWh, API calls, ride credits, consultation hours — any measurable service.

1. Define
Credit quota

→

2. Deploy
Live engine

→

3. Consume
CloudEvents

→

4. Report
Usage report

No DevOps required Auto-generated API Real-time analytics Internal quota mgmt

Who Uses Units360 Here

🎮 Acme Gaming

In this demo, the Organization is Acme Gaming — an enterprise that provides AI tools to employees across engineering, content, and game design teams. Their IT department uses Units360 to manage AI spend.

OrganizationAcme Gaming — enterprise AI tools admin

Use caseInternal AI credit quota — not external billing

Internal unitAI credit — company-defined quota currency

Quota per employee1,000 AI credits / month

Employee trackedJordan Chen — data science team

The IT admin logs into Units360, defines the AI credit unit with conversion rates for each backend service, and sets quotas per employee. Units360 then handles real-time tracking, threshold alerts, quota enforcement, and usage report generation automatically.

Credit Conversion Table

🔄 How Credits Convert

The AI credit is an internal quota currency. Each backend service reports its native units (tokens, video minutes), and Units360 converts them into credits automatically using the conversion table configured by IT.

LLM (GPT-4)200 tokens = 1 AI credit

LLM (Claude)150 tokens = 1 AI credit (higher quality tier)

VR Video Gen5 video minutes = 1 AI credit

Reset periodMonthly — credits reset on the 1st of each month

Hard quota1,000 AI credits — all services blocked at quota

IT can adjust conversion rates at any time — for example, making Claude cost more credits per token than GPT-4, steering employees toward cost-effective models — without touching any application code.

1 credit = 200 LLM tokens 1 credit = 5 VR min

Core Concept · 1 of 3

⚡ What is a Unit?

A Unit is the fundamental thing being measured. It defines what you are counting, how it accumulates, and when it resets.

unit_idai-credit — the unique identifier

display_nameAI Credit

directionUNIDIRECTIONAL — credits only consumed, never returned

reset_periodMonthly — quota resets on the 1st of each month

precision0 decimal places — credits are whole numbers

Units can be unidirectional (credits only consumed) or bidirectional (energy exported / imported). For AI credit quotas, direction is always inbound — each service call consumes credits from the employee's monthly allowance.

AI Credits · kWh · API Calls LLM Tokens · Video Minutes

Core Concept · 2 of 3

👤 What is an Account?

An Account is the entity whose usage is being tracked — an employee, a team, a device, or a tenant. Each account gets its own running credit balance governed by the configured quota.

account_idjordan.chen — employee ID

quotaStandard — 1,000 AI credits/month

alert_threshold80% usage — webhook fired to notify IT admin

hard_limit1,000 AI credits — all AI services blocked until next month

current_balanceLive credit count — updated per service call

When a service call arrives, Units360 looks up the account, converts native units to credits using the conversion table, updates the running total atomically, and fires threshold alerts when configured limits are crossed.

Core Concept · 3 of 3

📋 What is a Transaction?

A Transaction is a single metering event — one service call that reports "this employee consumed X native units right now." Units360 converts native units to AI credits and updates the running balance.

servicellm-gpt4 · vr-video-gen — service identifier

native_qty800 tokens or 10 video minutes — raw service output

credit_costCalculated by Units360: 800÷200 = 4 credits

balance_afterRunning credit total updated after each event

timestampISO 8601 UTC — every event is time-stamped precisely

Each transaction carries the native quantity (tokens or minutes) and the service type. Units360 applies the conversion rate from the configuration and updates the shared credit balance atomically.

At month end, all transactions are aggregated per service. The AI Credit Usage Report shows each service's native usage alongside its credit cost — no manual reconciliation needed.

Configuration Layer

📐 Usage Configuration

The Usage Configuration is Units360's low-code setup builder. IT defines everything about the AI credit quota model — with no code, no database schemas, no infrastructure setup.

Define it once, and it governs every service call, every balance update, and every usage report for that quota type.

Unit tabDefine the unit (ai-credit), direction (inbound), reset period (monthly)

Services tabAdd each backend service + its native unit + conversion rate to credits

Account tabSet per-employee quota, alert threshold (80%), hard limit (1,000 credits)

Reports tabConfigure usage report format, recipients, and reporting period

Once saved, Units360 auto-generates REST API endpoints for each service, CloudEvent schemas, and a live IT admin dashboard. No DevOps team required.

Event Protocol

📡 CloudEvents — The JSON Payload

Units360 uses the CloudEvents 1.0 spec. Every service call is formatted as a CloudEvent JSON payload and POSTed to the Units360 live endpoint. Units360 converts to AI credits on the fly.

// LLM gateway → Units360 (one call = 800 tokens) POST /api/v1/events/jordan.chen Content-Type: application/cloudevents+json { "specversion": "1.0", "type": "com.units360.ai.credit", "source": "llm-gateway/jordan.chen", "time": "2026-05-14T10:22:18Z", "data": { "service": "llm-gpt4", "native_unit": "tokens", "qty": 800 } } // Units360 converts: 800 ÷ 200 = 4 AI credits deducted

specversionAlways "1.0" — CloudEvents standard version

sourceService gateway + employee ID — where the call originated

data.serviceService identifier — maps to a conversion rate in config

data.native_unit"tokens" or "video_minutes" — the service's native measurement

data.qtyNative quantity — Units360 converts to AI credits automatically