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

# Introduction

> Real-time observability for AI coding agents, autonomous workflows, and production LLM apps — with per-user cost attribution.

Voight captures every prompt, tool call, model response, decision, and on-chain transaction your agents and AI applications make. The dashboard renders them as a live timeline. The explorer makes selected agents publicly discoverable on Solana.

If you ship LLM features to end-users, Voight also answers the question nobody else does cleanly: **what does each user cost me?** One line of code at your request boundary, no PII handoff required — full pattern on the [per-user spend](/concepts/per-user-spend) page.

## Five surfaces, one event stream

| Surface        | Lives at                                                              | What it's for                                                                                                                         | Reference                                                                                     |
| -------------- | --------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------- |
| **Dashboard**  | `voight.xyz/dashboard`                                                | Live timeline, agents, alerts, cost + token KPIs                                                                                      | [Events](/concepts/events)                                                                    |
| **AI Apps**    | `voight.xyz/dashboard/ai-apps`                                        | Production LLM-app observability — Overview / Traces / Models / Tools / Users                                                         | [AI Apps overview](/ai-apps/overview)                                                         |
| **Explorer**   | `voight.xyz/explore`                                                  | Public agent profiles, on-chain identity, reputation                                                                                  | [Agents](/concepts/agents)                                                                    |
| **Coding SDK** | `@voightxyz/sdk` on npm                                               | Hook Claude Code or Cursor (Codex in active fix), or any TS/JS agent you build yourself                                               | [Quickstart](/quickstart)                                                                     |
| **App SDKs**   | `@voightxyz/openai` · `@voightxyz/anthropic` · `@voightxyz/vercel-ai` | Capture LLM calls from production apps — direct provider wrappers or via the Vercel AI SDK                                            | [OpenAI](/ai-apps/openai) · [Anthropic](/ai-apps/anthropic) · [Vercel AI](/ai-apps/vercel-ai) |
| **Python SDK** | `bitfrost` on PyPI                                                    | Drop-in OpenTelemetry observability for Python LLM apps — openai / anthropic / litellm / smolagents, standalone or shipping to Voight | [Bitfrost](/python/bitfrost)                                                                  |
| **HTTP API**   | `POST /v1/events`                                                     | Language-agnostic event ingestion — Python, Go, Rust, anything                                                                        | [API reference](/api-reference/events)                                                        |

## What Voight is for

Three audiences, one product:

* **You're building an AI coding agent or autonomous bot.** Wire the [coding SDK](/quickstart) into your IDE or import [library mode](/sdk/library-mode) — every prompt, tool call, error, and Solana tx lands in the dashboard with zero code changes.
* **You're shipping an LLM-powered feature to end-users.** Wrap your OpenAI / Anthropic client with the [App SDKs](/ai-apps/openai), or register [`@voightxyz/vercel-ai`](/ai-apps/vercel-ai) once if you're on the [Vercel AI SDK](https://sdk.vercel.ai). Every call gets captured with full token/cost breakdown. Add [`withTrace`](/ai-apps/tracing) at your request boundary to group calls per request and attribute cost per end-user.
* **You sell AI-powered tools to other developers.** The [per-user spend](/concepts/per-user-spend) pattern lets you answer "what does each of my customer's customers cost me?" without integrating an analytics SDK on the client side.

## Primitives

* **Agent** — an autonomous entity emitting events. Identified by a folder marker, env var, or explicit `agentId`.
* **Event** — a single observation: prompt, tool call, decision, error, cost record.
* **Trace** — a group of events sharing a `traceId`, typically one user request or workflow.
* **Session** — a time-bounded run of an agent.
* **Tag** — a free-form `key=value` pair attached to events inside a [`withTrace`](/ai-apps/tracing) block; the foundation of per-user / per-tenant / per-feature attribution.

## Privacy

Three capture levels — **Minimal** (metadata only), **Standard** (full content with local PII scrubbing), **Full** (raw). Picked once at install, switchable per session via env var. The dashboard renders a per-event chip showing which level captured each row.

The numeric data — tokens, USD, latency, tool names, tags — passes through every level unchanged. KPIs and charts work identically in all three. You only lose prompt/response content in Minimal.

See the [privacy overview](/privacy/overview) for the field-by-field breakdown.

## Next

* [Quickstart](/quickstart) — events streaming in 30 seconds (any of four install paths)
* [AI Apps overview](/ai-apps/overview) — the dashboard section for production LLM apps
* [Per-user spend](/concepts/per-user-spend) — one line of code to attribute cost per end-user