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
Conversation-native
Built for customer service across voice and chat. Add raw information to your knowledge – Raven converts it into natural conversational responses without extra prompting.
Faster
Sub-300ms median latency. Consistent response times – no long-tail spikes.
More accurate
Higher accuracy on PolyAI’s customer service benchmarks. Fewer errors in tool calling and knowledge grounding.
Multilingual
24+ languages with near-perfect language consistency. Set the response language – Raven speaks it, even with English-only prompts.
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 earlier Raven versions, with near-perfect language consistency
Raven V3 is deprecated. Older Raven versions now route to Raven 3.5 automatically. Existing deployments keep working, but you should select Raven 3.5 directly in your agent configuration.
Supported languages
Raven supports the following languages:- All languages
- Strongest performance
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
Getting started
Select Raven 3.5 in Voice configuration or Chat configuration.Related pages
Model selection
Compare Raven with OpenAI and Amazon Bedrock models.
Training data
Transparency on datasets used to train Raven.
Bring your own model
Connect your own LLM endpoint to PolyAI.

