IN-PROCESS AI FINOPS

AI cost monitoring that runs inside your application.

AI cost monitoring is the process of measuring the provider cost of AI model requests and associating that cost with the application action that caused it. VibezCheck provides this measurement in-process for TypeScript applications.

What AI cost monitoring should tell you

What did this request cost?

Calculate exact micro-dollar provider cost from prompt, completion, cached, and reasoning usage.

Which model generated the cost?

Track spending across GPT-4o, Claude 3.5 Sonnet, Gemini 1.5 Pro, DeepSeek R1, and local models.

Which customer caused it?

Attribute usage directly to user IDs, enterprise workspaces, and billing accounts.

Which feature caused it?

Tag telemetry by featureId (e.g. smart-search, summary-v2, chat, code-review).

How much did this agent session spend?

Measure cumulative multi-turn costs across recursive agent loops and tool calls.

Can the request exceed its budget?

Enforce hard caps in the execution path before costs spiral into unexpected cloud invoices.

Why token counts are not enough

Token counts are raw engineering units. A million tokens of DeepSeek R1 cost $0.55, while a million output tokens of OpenAI o1 cost $60.00.

Furthermore, modern providers introduce complex rate structures: prompt cache discounts (50% to 90% cheaper), reasoning tokens billed at output rates, and multimodal tokens. Without model-aware financial math, raw token counters cannot tell you whether a user interaction was profitable or bankrupting.

VibezCheck translates tokens + model rates + discounts → real dollars.

Track cost by customer & tenant

Attach identifiers in the application path. Every telemetry event carries full organizational context for granular ledger reporting:

import { streamText } from 'ai';
import { openai } from '@ai-sdk/openai';
import { vibezcheck } from 'vibezcheck';

const result = streamText({
  model: vibezcheck(openai('gpt-4o-mini'), {
    customer: 'tenant_enterprise_42',
    organization: 'acme_corp',
    featureId: 'smart_contracts_audit',
    threadId: 'session_8921_abc',
    maxCostPerCallUSD: 0.25,
  }),
  prompt: contractText,
});

Control runaway spend

Autonomous agents and recursive tool loops can generate hundreds of API requests in seconds. VibezCheck stops runaway loops with in-process limits like maxCostPerCallUSD and multi-step session ceilings:

Request-Level Fuse

Instantly terminates model calls that exceed your allocated dollar ceiling.

Agent Session Budget

Tracks cumulative spend across model and tool invocations with a hard stop.

Connect cost to billing

Once your application measures provider cost, you can feed those events into Stripe, Metronome, or your billing database to monetize AI usage.

Explore AI usage-based billing·Try LLM Cost Calculator

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