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

# Answer

<p style={{ fontSize: "0.8rem", opacity: 0.6 }}>For AI agents: <a href="https://docs.octen.ai/capabilities/answer.md">docs.octen.ai/capabilities/answer.md</a></p>

Getting from a question to a grounded answer takes a pipeline: decompose the question, run the searches, feed results to a model, synthesize, and keep track of sources.

Octen Answer runs that pipeline in one call: it decomposes your messages into sub-queries, searches them, and synthesizes an answer with an LLM, returning the sources it used.

For the full list of parameters, see the [Answer API reference](/api-reference/answer).

## Why Answer

* **One call, complete loop.** A question goes in; a grounded answer comes out. No search, prompt, and synthesis plumbing to build or maintain.
* **Multi-angle grounding.** Questions decompose into multiple sub-queries, so the answer draws on wider coverage.
* **Citable answers.** The sub-queries and sources come back with the answer, so replies can link to the pages they stand on.

To run synthesis in your own stack, use [Broad Search](/capabilities/broad-search). For long-form research reports, use [Deep Research](/capabilities/deep-research).

## How It Works

1. Send a question or a conversation.
2. Octen decomposes it into sub-queries and searches them concurrently.
3. A model synthesizes an answer grounded in the results; the response returns the answer together with the sub-queries and sources used.

## Scenarios

### Ask a question

One message in, one grounded answer out, with the sub-queries and sources it drew on.

```bash theme={null}
curl -X POST https://api.octen.ai/answer \
  -H "Content-Type: application/json" \
  -H "x-api-key: YOUR_API_KEY" \
  -d '{
    "messages": [{ "role": "user", "content": "What changed in the EU AI Act this year?" }]
  }'
```

### Build a grounded chat assistant

In a conversation, questions build on each other. Pass the chat history along, and every reply stays grounded in live search, with follow-ups understood in context.

```json theme={null}
{
  "messages": [
    { "role": "user", "content": "What are the current US tariffs on Chinese EVs?" },
    { "role": "assistant", "content": "The current rate is..." },
    { "role": "user", "content": "How does the EU compare?" }
  ]
}
```

### Get the full picture on a broad topic

Some questions are really many questions: a market, a technology, a policy area. Answer decomposes them into up to 30 sub-queries and returns a structured Markdown answer that covers the topic angle by angle, cited throughout.

```json theme={null}
{
  "messages": [{ "role": "user", "content": "the state of the European EV market in 2026" }]
}
```

### Answer from sources you trust

When answers must stand on vetted sources, such as in finance or news products, constrain the searches behind the answer. Answer accepts the same search options as Web Search.

```json theme={null}
{
  "messages": [{ "role": "user", "content": "central bank rate decisions this week" }],
  "web_search_options": {
    "include_domains": ["reuters.com", "bloomberg.com"],
    "time_range": "week"
  }
}
```

## Next Steps

<CardGroup cols={2}>
  <Card title="Try in Console" icon="play" href="https://octen.ai/platform/answer">
    Run Answer live in the Octen console.
  </Card>

  <Card title="Answer API Reference" icon="code" href="/api-reference/answer">
    Full request/response schema.
  </Card>
</CardGroup>
