Loading page
MetricAIMetricAI
AI Infrastructure

Meter every AI call, enforce budgets, and bill customers accurately - across every provider.

One SDK for real-time usage attribution, streaming-safe metering, provider routing, and an auditable billing ledger.

Start free - meter your first AI call in 5 minutesWatch a 2-minute product tour
No credit card requiredTalk to an AI billing architect →
Append-only
Double-entry, reconcilable ledger
Non-blocking
Async metering off the request path
19
Providers, frameworks & voice APIs

Metering runs asynchronously so it does not sit in your request path. See how the layer is built.

metricai.co.in / livestreaming
Tokens metered
1,248,302
▲ 12.4% vs yesterday
Billed usage
$43.28
last 60s window
The Infrastructure Layer

Without MetricAI

AppProvider
  • No metering
  • No observability
  • No cost attribution
  • No ledger
  • No budget enforcement

With MetricAI

AppProvider
  • Metering
  • Observability
  • Cost attribution
  • Ledger
  • Budget enforcement
Near-zero latency

One integration layer for metering, billing, routing, and observability across every AI provider.

Built for modern AI infrastructure

One SDK for supported providers. One event API for everything else.

ElevenLabs
Sarvam AI
OpenAI
Anthropic
Google Gemini
Vertex AI
AWS Bedrock
Azure
Mistral
Grok
Groq
Tavily
CrewAI
LlamaIndex
AutoGen
LiveKit
Deepgram
LangChain
ElevenLabs
Sarvam AI
OpenAI
Anthropic
Google Gemini
Vertex AI
AWS Bedrock
Azure
Mistral
Grok
Groq
Tavily
CrewAI
LlamaIndex
AutoGen
LiveKit
Deepgram
LangChain
Browse all 19 integrations
Capabilities

Built for the searches AI teams actually make

If you are looking for AI usage metering, LLM cost attribution, agent billing, or budget enforcement - this is the infrastructure layer those problems need.

AI usage metering

Meter every AI call in real time across models, agents, and features - including streaming responses - so usage lands in an auditable ledger as it happens.

LLM cost attribution

Attribute OpenAI, Anthropic, Gemini, and other LLM spend to customers, workspaces, agents, and sessions instead of reconciling provider invoices weeks later.

AI agent billing

Bill autonomous agents by tokens, tool calls, outcomes, or hybrid rules with idempotent invoice runs built for production traffic.

OpenAI, Anthropic, and Gemini metering

One SDK meters supported LLM providers with a shared unit model and price book, so routing changes do not break cost estimates.

Voice AI billing

Meter Deepgram, ElevenLabs, LiveKit, and other voice stacks as one conversation - audio minutes, tokens, and tool calls on a single timeline.

BYOK AI gateway

Bring your own provider keys, route through MetricAI for metering and governance, and keep credentials encrypted under your control.

AI spend controls and budget enforcement

Enforce hard and soft budgets per agent, user, or workspace in the request path so runaway agents are stopped before they become an invoice.

Usage-based billing for AI SaaS

Turn metered AI usage into customer invoices with outcome-based or hybrid pricing and UPI-native settlement for Indian collections.

Explore use cases →Browse integrations →Compare approaches →
Incubated atIIT Mandi iHub & HCi Foundation
The problem

AI billing breaks at scale

The infrastructure primitives for AI usage don't exist in traditional billing systems.

Runaway AI costs

Long-running agents can burn through monthly budgets in minutes without real-time visibility.

Complex attribution

Multi-provider AI stacks make accurate cost attribution across users, agents and workflows difficult.

Legacy billing breaks

Traditional billing systems were never designed for token-based, streaming AI workloads.

What we provide

The infrastructure layer for AI billing

Everything you need between your application and AI providers.

Real-time AI metering

Measure every request, token, completion and provider usage in real time.

Ledger integrity

Immutable financial records with complete auditability and reconciliation.

Idempotent APIs

Safe retries with cryptographic keys prevent duplicate billing events.

Provider abstraction

Integrate once. Work across OpenAI, Anthropic, Gemini, Bedrock and more.

Lightweight SDK

Drop into Python or Node.js in a few lines. No infra to run.

Production ready

Designed for high-throughput AI systems that demand precision.

Use cases

Where teams put us to work

Four problems that keep showing up once AI hits production traffic.

03

Voice-agent billing

Meter audio minutes, tokens, and tool calls as one session.

Read the scenario
See it work

A two-minute look at the product

Watch the tour, then poke at a live slice of the dashboard below. Same layout you get on day one.

Product tour is being recorded

Rather than ship a fake player, we would rather walk you through it live - or you can start free and see it yourself in five minutes.

Get a live walkthroughStart free instead
Sample dashboard · illustrative data
CustomerCallsCostMargin
Northwind AI41,230$812.4068%
Kettle Labs18,902$1,240.9041%
Voxa Support9,640$508.1555%
Finlyt4,310$96.7074%

Figures are illustrative sample data, not customer data. Click a row to switch the breakdown.

Architecture

How MetricAI works

A single infrastructure layer between your application and every AI provider you use.

Layer 1
Your Application
SDK · REST
Layer 2
MetricAI Layer
Meter · Route · Ledger
Layer 3
AI Providers
LLM · Voice · Vision
Ledger
Append-only, double-entry, reconcilable
Metering
Streaming token & event capture
Billing API
Idempotent invoice + usage export
For developers

Integrate in minutes,
not months.

Lightweight SDKs for Python and Node.js. Provider-agnostic, streaming-native, and idempotent by default. Meter every token without touching your business logic.

  • Wrap any AI provider with a single client
  • Automatic token & cost capture, streaming safe
  • Idempotency keys on every billable event
  • Type-safe usage export to your billing system
Integrate MetricAI in minutes.
$pip install metricai openai
import os
import metricai
from openai import OpenAI

metricai.init(
    api_key=os.getenv("METRICAI_API_KEY"),
    auto_instrument=True,
    default_agent_id="weather-bot",
    default_user_id="user_123",
    llm_keys={"openai": os.getenv("OPENAI_API_KEY")},
)

client = OpenAI()
resp = client.chat.completions.create(
    model="gpt-4o",
    messages=[
        {
            "role": "user",
            "content": "What is the current weather in Tokyo?"
        }
    ],
)

print(resp.choices[0].message.content)

Works with OpenAI, Gemini, Anthropic, Vertex AI, Bedrock, LiveKit, Deepgram, ElevenLabs, Sarvam AI, and other supported providers through a unified SDK.

Capabilities

Everything you need in one layer

A complete billing and metering surface for token-based AI workloads.

Real-time metering
Usage attribution
Ledger integrity
Idempotent APIs
Provider routing
Cost visibility
Python SDK
Node.js SDK
Multi-provider support
High throughput
Enterprise reliability
Developer experience
Integrations

One SDK. Every provider.

One SDK for supported providers. One event API for everything else.

LLM providers

9 integrations
  • OpenAI
  • Anthropic
  • Google Gemini
  • Grok
  • Groq
  • Mistral
  • Vertex AI
  • Azure Foundry
  • Bedrock

Agentic frameworks & tools

6 integrations
  • CrewAI
  • LangChain
  • LangGraph
  • LlamaIndex
  • AutoGen
  • Tavily

Voice & realtime

4 integrations
  • LiveKit
  • Deepgram
  • ElevenLabs
  • Sarvam AI
Browse all 19 integrations
FAQ

Common questions about AI metering and billing

Straight answers for teams evaluating usage metering, cost attribution, and spend controls.

What is AI usage metering?

AI usage metering measures every AI call - tokens, audio minutes, tool invocations, and outcomes - in real time so you can attribute cost and bill accurately.

How does MetricAI handle LLM cost attribution?

MetricAI attributes OpenAI, Anthropic, Gemini, and other provider spend to customers, agents, workspaces, and sessions at request time, with an append-only ledger for reconciliation.

Can MetricAI bill AI agents and voice stacks?

Yes. Meter autonomous agents and voice sessions that span Deepgram, ElevenLabs, LiveKit, LLMs, and tools as one billable conversation or workflow.

What is a BYOK AI gateway?

Bring Your Own Key means you keep provider credentials while MetricAI sits in the request path to meter usage, enforce budgets, and optionally apply billing markups.

How do AI spend controls and budget enforcement work?

Soft alerts and hard caps are enforced in the proxy per agent, user, or workspace, so runaway spend is blocked before the upstream provider charges you.

Does MetricAI support usage-based billing for AI SaaS?

Yes. Export attributed usage into customer invoices, charge by usage or outcome, and settle natively in INR over UPI through Razorpay.

Ready to meter your first AI call?

Install the SDK, point it at your provider, and watch usage land in the ledger. The same integration carries you from prototype to production.

Start free - 5 minutes to first callTalk to an AI billing architect

No credit card required · Cancel or downgrade at any time