> ## Documentation Index
> Fetch the complete documentation index at: https://docs.captar.aurat.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Overview

> The shortest path to a working Captar integration for a TypeScript app using OpenAI.

# Getting Started Overview

Captar fits into an existing Node or TypeScript app. You create a runtime,
start sessions around request-level work, wrap your OpenAI client, and attach
an exporter when you want traces and spend events to reach the platform.

The mental model is simple:

* A runtime owns project-level defaults and export settings.
* A session carries budget, policy, and trace context for one unit of work.
* A wrapped OpenAI client makes the request safe to observe and constrain.
* Tool tracking keeps external actions inside the same trace.

## Prerequisites

* Node.js 20 or later
* A TypeScript or JavaScript application
* An OpenAI API key
* Optional platform ingest URL if you want exported traces

## Recommended path

<Steps>
  <Step>Install `@captar/sdk` and `openai`.</Step>
  <Step>Create a Captar runtime for your project.</Step>
  <Step>Start a session with budget, metadata, and policy.</Step>
  <Step>Wrap your OpenAI client and make model calls through that session.</Step>
  <Step>Track external tools and close the session when work completes.</Step>
</Steps>

<Callout title="SDK-first docs">
  The fastest way to understand Captar is to build one successful session end to
  end, then read the runtime model and reference sections.
</Callout>

## When Captar is a good fit

* You want budget controls inside the app process rather than outside it.
* You already have an OpenAI client and do not want to rewrite the integration.
* You care about trace quality and later review of strong or blocked runs.
* You need a straightforward path from production traces into manual evals.