LLM Analytics

LLM Analytics for
Production AI Applications

Understand how your LLM features behave in production. Track costs, latency, errors, and usage patterns across OpenAI, Anthropic, and Gemini.

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What is LLM Analytics?

LLM analytics gives you visibility into how your AI features perform in production. It's the answer to "What's happening with our AI?"

Cost Analytics

Track spend by feature, model, and customer

Latency Tracking

Monitor response times and identify slow features

Error Monitoring

Catch and analyze API errors before users complain

Usage Patterns

Understand how features are being used

Key LLM Metrics to Track

Orbit captures the metrics that matter for understanding and optimizing your LLM usage.

$2,400

Monthly cost

1.2M

Tokens used

342ms

P50 latency

0.3%

Error rate

Cost per feature

Chat assistant: $1,200
Doc analyzer: $800
Code helper: $400

Cost per model

GPT-4o: $1,800
Claude 3.5 Sonnet: $400
GPT-4o-mini: $200

Cost per customer

Enterprise A: $500
Enterprise B: $300
Others: $1,600

Multi-Provider LLM Analytics

Most teams use multiple LLM providers. Orbit gives you a unified view across all of them.

OpenAI

GPT-4o
GPT-4o-mini
o1
Embeddings

Anthropic

Claude 3.5 Sonnet
Claude 3.5 Haiku
Claude 3 Opus

Google

Gemini 1.5 Pro
Gemini 2.0 Flash
Gemini 1.5 Flash

Add LLM Analytics in Minutes

Wrap your LLM client with Orbit's SDK and start seeing analytics immediately.

Node.js / Python

import { Orbit } from '@with-orbit/sdk';

const orbit = new Orbit({ apiKey: 'your-orbit-key' });

// Wrap any LLM client
const openai = orbit.wrapOpenAI(new OpenAI(), {
  feature: 'your-feature-name'
});

const anthropic = orbit.wrapAnthropic(new Anthropic(), {
  feature: 'your-feature-name'
});

const gemini = orbit.wrapGemini(new GoogleGenerativeAI(), {
  feature: 'your-feature-name'
});

// Use normally - analytics are captured automatically