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

# Welcome to Brixo

> Brixo transforms AI agent conversations into business-ready insights about user intent, experience, and outcomes.

## What is Brixo?

Brixo helps Product, Support, Sales, and Executive teams understand what’s really happening inside AI-powered conversations.

Brixo answers three fundamental questions:

1. **Why users engage with AI agents** — their goals and intent
2. **How users experience those interactions** — sentiment, effort, friction
3. **What outcomes those interactions produce** — resolution, containment, deflection, CSAT

Brixo bridges the gap between **engineering telemetry** and **business outcomes** by transforming raw conversational data into structured signals and KPIs teams can act on.

> Brixo is not an engineering observability tool.\
> We use telemetry as an input to measure **human experience and business impact**.

***

## What Brixo Measures

Brixo analyzes conversations using two layers:

### Signals (what happened)

* User Goals (e.g. *Reset Password*, *Cancel Subscription*)
* Conversation Topics (e.g. *Billing*, *Technical Support*)
* User Sentiment
* Conversational Events (loops, escalations, abandonments, wins)

### Metrics (why it matters)

* Resolution Rate
* First Contact Resolution (FCR)
* Effort Score
* CSAT / Health
* Containment / Automation Success
* Deflection Rate
* Average Handle Time (AHT)

These metrics map directly to executive dashboards, operational reporting, and ROI analysis.

***

## Choose Your Integration Path

Brixo supports **two first-class ways** to send conversation data.\
Both are valid — choose based on how your system is built today.

***

## Path 1 — Use the Brixo SDK (Explicit Conversation Instrumentation)

Best for teams who want **maximum accuracy and control** over how conversations are represented.

With the Brixo SDK, you explicitly define:

* Interaction boundaries (one user request → one response)
* User, account, and session identity
* User-visible input and final agent output

This guarantees that Brixo sees the conversation exactly as the user experienced it.

**Recommended if:**

* You want precise resolution, effort, and health metrics from day one
* You control the agent runtime
* You want minimal inference and maximum correctness

→ **Get started:** `/quickstart/python`

***

## Path 2 — Use Your Existing OpenTelemetry (OTLP) Integration

Best for teams who already emit OpenTelemetry traces and want to **get started quickly**.

Brixo can ingest traces directly via **OTLP** (HTTP or gRPC).\
You can stream your existing traces to Brixo without changing your observability stack.

This path supports **progressive enrichment**:

* Start by sending what you already emit
* Layer in lightweight context over time to unlock deeper analytics

**Recommended if:**

* You already use OpenTelemetry (e.g. Pydantic AI, framework auto-instrumentation)
* You want minimal upfront integration work
* You plan to evolve instrumentation incrementally

→ **Get started:** `/quickstart/otlp`

> OTLP is the transport.\
> Conversation Analytics depends on whether traces reflect **complete user interactions**.

***

## Progressive Enrichment (Applies to Both Paths)

You don’t need perfect instrumentation on day one.

A common progression:

1. Send existing data (SDK or OTLP)
2. Validate interaction boundaries
3. Add user/session context
4. Add explicit user-visible input/output
5. Unlock full experience and outcome analytics

Brixo will guide you on the **smallest possible additions** needed to unlock more value.

***

## Which Path Should I Choose?

| If you want…                                  | Choose…          |
| --------------------------------------------- | ---------------- |
| Fastest start with existing telemetry         | OTLP Integration |
| Guaranteed accuracy for conversation metrics  | Brixo SDK        |
| No changes to your observability stack        | OTLP Integration |
| Explicit control over conversation boundaries | Brixo SDK        |

You can also **combine both** — many teams start with OTLP and later add lightweight SDK instrumentation for richer context.

***

## Next Steps

* **Using OpenTelemetry?** → `/quickstart/otlp`
* **Instrumenting an agent directly?** → `/quickstart/python`
* **Questions?** → [hello@brixo.com](mailto:hello@brixo.com)

***

### Key Takeaway

**Brixo measures conversations — not just traces.**\
Choose the integration path that fits your system today, and evolve from there.