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

# Raven

> PolyAI's proprietary LLM family, built for customer service across voice and chat.

Raven is PolyAI's proprietary LLM, built for real-time customer conversations. Sub-300ms latency, stronger grounding, and more natural responses than general-purpose LLMs. 24+ languages.

Raven powers the majority of PolyAI deployments. You can select it in [Voice configuration](/voice/voice-configuration) and [Chat configuration](/webchat/chat-configuration), or compare it with other options on the [Model](/agent-settings/model-use) page.

## Why Raven

General-purpose models (GPT, Claude) are trained for broad text use cases. They need extensive prompting for customer service and can still be unreliable. Raven is built for this – the right conversational behavior is built in.

General-purpose models are:

* Slower – large models handling everything
* Text-first – trained on chat, not phone conversations
* Hard to tune – require heavy prompting for voice use cases

Raven is faster, more natural, and more reliable because customer service is all it does.

<CardGroup cols={2}>
  <Card title="Conversation-native" icon="comments">
    Built for customer service across voice and chat. Add raw information to your knowledge – Raven converts it into natural conversational responses without extra prompting.
  </Card>

  <Card title="Faster" icon="bolt">
    Sub-300ms median latency. Consistent response times – no long-tail spikes.
  </Card>

  <Card title="More accurate" icon="bullseye">
    Higher accuracy on PolyAI's customer service benchmarks. Fewer errors in tool calling and knowledge grounding.
  </Card>

  <Card title="Multilingual" icon="globe">
    24+ languages with near-perfect language consistency. Set the response language – Raven speaks it, even with English-only prompts.
  </Card>
</CardGroup>

### Additional capabilities

**Date and time logic** – handles relative dates, scheduling, and format conversions that trip up general-purpose models.

**Reliable tool calling** – trained on real Agent Studio projects. Calls functions with correct parameters; doesn't confuse responding with acting.

**No hallucination** – grounded in your knowledge. Says "I don't know" rather than inventing answers.

**Agent Studio native** – understands topics, flows, and PolyAI's knowledge retrieval patterns by default.

## Raven 3.5

Latest Raven model. Supports voice and chat. Recommended for all new deployments.

* **Auto-reasoning** – automatically decides when to think deeper before responding, improving accuracy on complex tasks like date calculations without adding latency on simple turns
* **Out-of-domain detection** – identifies when a request falls outside the agent's scope, enabling cleaner handoffs and knowledge gap tracking
* **Built-in safety** – guardrails against misuse, with built-in protection against hallucinations
* **Custom style following** – respects custom persona and style instructions, including emotion tags for TTS, formatting rules, and channel-specific tone
* **24+ languages** – more natural multilingual outputs than V3, with near-perfect language consistency

<Note>
  **Raven V3** is a legacy model superseded by Raven 3.5. It supports the same 24 languages but lacks auto-reasoning, out-of-domain detection, chat support, and the safety and style improvements in 3.5. Raven 3.5 outperforms V3 in all scenarios – there is no use case where V3 is the better choice. V3 remains available in [Voice configuration](/voice/voice-configuration) for existing deployments that have not yet migrated.
</Note>

## Supported languages

Raven supports the following languages:

<Tabs>
  <Tab title="All languages">
    Arabic, Bulgarian, Cantonese, Croatian, Czech, Dutch, English, French, German, Greek, Hindi, Hindi (Romanized/Hinglish), Italian, Japanese, Korean, Mandarin (China), Mandarin (Taiwan), Polish, Portuguese (Brazil), Portuguese (Portugal), Serbian, Spanish (US), Swedish, Turkish
  </Tab>

  <Tab title="Strongest performance">
    These languages show particularly strong performance relative to general-purpose models: Cantonese, Italian, Korean, Mandarin (China), Mandarin (Taiwan), Spanish (US)
  </Tab>
</Tabs>

<Tip>
  You can keep all your prompts and knowledge in English and set the response language to your target language. Raven responds consistently in the target language. Quality improves further if you translate prompts and add examples in the target language.
</Tip>

## Getting started

Select **Raven 3.5** in [Voice configuration](/voice/voice-configuration) or [Chat configuration](/webchat/chat-configuration).

## Related pages

<CardGroup cols={3}>
  <Card title="Model selection" icon="sliders" href="/agent-settings/model-use">
    Compare Raven with OpenAI and Amazon Bedrock models.
  </Card>

  <Card title="Training data" icon="database" href="/legal/training-data">
    Transparency on datasets used to train Raven.
  </Card>

  <Card title="Bring your own model" icon="plug" href="/agent-settings/byom">
    Connect your own LLM endpoint to PolyAI.
  </Card>
</CardGroup>