---
title: Introduction
description: Welcome to Latitude, the Agent Observability Platform
---

# Introduction

Latitude is an open-source **agent observability platform**. It helps teams turn live agent traffic and human judgment into measurable, improvable quality. So you can ship AI features with confidence.

## What Latitude Does

Latitude gives you a closed-loop system for monitoring, evaluating, and improving AI agents in production:

- **Observe**: Capture every interaction your agents have with users through automatic telemetry. See spans, traces, and sessions in real time.
- **Score**: Attach quantitative verdicts to every interaction. Scores come from automated evaluations, human annotations, or your own custom logic.
- **Discover**: When scores indicate failures, Latitude automatically groups similar problems into **issues**: named, trackable failure patterns.
- **Evaluate**: Generate monitoring scripts from discovered issues. These evaluations run continuously on live traffic, catching regressions before users notice.
- **Align**: Keep your automated evaluations honest by measuring how well they agree with human reviewers. Latitude tracks alignment metrics so you know when machine judgment drifts from human judgment.
- **Simulate**: Before shipping changes, run your agent against test scenarios locally or in CI. Reuse the same evaluation scripts that monitor production.
- **Improve**: Use everything you've learned to make your agents better, then repeat.

## How It All Connects

Every feature in Latitude feeds the next. Observability captures interactions. Evaluations score them. Failed scores surface issues. Issues generate new evaluations. Human annotations keep evaluations calibrated. Simulations prevent regressions before they reach production.

The result is a continuous improvement cycle where your agents get better with every interaction.

## Key Concepts

| Concept           | What It Is                                                                                 |
| ----------------- | ------------------------------------------------------------------------------------------ |
| **Span**          | A single unit of work captured by telemetry (an LLM call, a tool invocation, etc.)         |
| **Trace**         | A complete interaction from start to finish, composed of one or more spans                 |
| **Session**       | A multi-turn conversation between a user and your agent, composed of related traces        |
| **Score**         | A quantitative verdict on a trace: normalized between 0 and 1, with pass/fail and feedback |
| **Evaluation**    | A script that automatically produces scores from your agent's interactions                 |
| **Issue**         | A named failure pattern discovered by grouping similar failed scores                       |
| **Annotation**    | A verdict on a trace from a human, a flagger, or the API, attached as a score              |
| **Flagger**       | A built-in automatic annotator for a known failure category like _jailbreaking_ or _frustration_ |
| **Search**        | A hybrid keyword + semantic search over trace conversations, with optional saved filters   |
| **Saved Search**  | A named bookmark for a search query plus filters, with assignee and review progress        |
| **Simulation**    | A test run of your agent against scenarios, evaluated locally or in CI                     |

## Next Steps

- **New to Latitude?** Read [Core Concepts](./concepts) to understand organizations, projects, and how everything fits together.
- **Developers**: Follow the [Developer Quick Start](./quick-start-dev) to connect your first agent and see traces in Latitude.
- **Team leads and PMs**: Follow the [No-Code Quick Start](./quick-start-pm) for a walkthrough of the Latitude web UI.
