See what needs to be fixed in your AI agent

Latitude traces every step your agent takes — every tool call, every reasoning turn — so when something breaks, you know exactly where in the chain it went wrong.

Under

10 minutes

to full agent trace visibility

Save up to

80% of time

going through logs manually

Most observability tools are built for APIs, not agents. Latitude is different.

Other observability tools tell you something failed. Latitude tells you where in the chain, and why.

Multi-step traces

See where in the chain your agent went wrong, not just what it returned

Tool call visibility

Know exactly which tool was called, with what input, and what it returned

Reasoning observability

Follow your agent's decision path turn by turn

Observability

Failure detection

Issue monitoring

Observability

Capture real inputs, outputs, and context from live traffic. Understand what your system is actually doing, not what you expect it to do.

Full traces

Observe your AI’s behaviour in the most comprehensive way

Usage statistics

Keep track of the token usage and regulate expenses

Observe

Monitor agent behaviour

Capture real inputs, outputs, and context from live traffic to understand what your agent is actually doing

Annotate

Flag what went wrong

Review real agent responses and annotate where things went off. That signal is what drives everything next.. Turn intent into a signal the system can learn from.

Reflect

See what keeps going wrong

Automatically group failures into recurring issues, detect common failure modes and keep an eye on escalating issues.

Start with visibility

Start with visibility. Grow into reliability.

Start the reliability loop with lightweight instrumentation. Go deeper when you’re ready.

Providers

• OpenAI
• Anthropic
• Azure
• Google AI Platform
• Amazon Bedrock
• Cohere
• Together AI
• Vertex AI
• Gemini
• Groq
• Mistral AI
• Ollama
• LiteLLM
• Replicate
• AWS SageMaker
• Hugging Face Transformers
• Aleph Aplha
• IBM watsonx.ai

import { LatitudeTelemetry } from '@latitude-data/telemetry'
import OpenAI from 'openai'

const telemetry = new LatitudeTelemetry(
  process.env.LATITUDE_API_KEY,
  { instrumentations: { openai: OpenAI } }
)

async function generateSupportReply(input: string) {
  return telemetry.capture(
    {
      projectId: 123, // The ID of your project in Latitude
      path: 'generate-support-reply', // Add a path to identify this prompt in Latitude
    },
    async () => {
      const client = new OpenAI()
      const completion = await client.chat.completions.create({
        model: 'gpt-4o',
        messages: [{ role: 'user', content: input }],
      })
      return completion.choices[0].message.content
    }
  )
}

Instrument once

Add OTEL-compatible telemetry to your existing LLM calls to capture prompts, inputs, outputs, and context.

This gets the loop running and gives you visibility from day one

Learn from production

Review traces, add feedback, and uncover failure patterns as your system runs.

Steps 1–4 of the loop work out of the box

Go further when it matters

Use Latitude as the source of truth for your prompts to enable automatic optimization and close the loop.

The full reliability loop, when you’re ready

Integrations

Integrates with your stack

Latitude is compatible with the majority of the platforms used to build LLM systems

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FAQ

Asnwer to the most popular questions

What's the difference between LLM observability and regular logging?

Do I need observability if my LLM app is already working fine?

How is Latitude different from Langfuse or other observability tools?

How quickly can I see my first production traces?

What issues will observability actually help me catch?

We're already using OpenAI's dashboard. Why do I need more?

Once I can see issues, then what?

Is there a free trial?