What does truly multilingual CX sound like?
About the show
Hosted by Nikola Mrkšić, Co-founder and CEO of PolyAI, the Deep Learning with PolyAI podcast is the window into AI for CX leaders. We cut through hype in customer experience, support, and contact center AI — helping decision-makers understand what really matters.
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Summary
Every customer expresses themselves differently, and their choice of language is no exception. So how can brands bridge the gap when customers come to them speaking different languages?
In this episode of Deep Learning with PolyAI, Jenn Cunningham sits down with Matt Henderson, VP of Research, and Viola Lin, Product Manager, to explore the evolution of multilingual voice AI and what it means for global customer experience.
They unpack what “multilingual” really means in practice — from accurate translation to cultural intelligence — taking PolyAI’s AI models and Agent Studio platform as a starting point to discuss helping enterprises deploy agents that sound natural, respectful, and consistent in over 45 languages.
They explore:
- Why multilingual CX should factor in much more than just translation, including cultural nuances
- How PolyAI handles dozens of languages in a single deployment
- Real-world challenges and what to do about them: from accents and formality to tone and gendered language
- The role of fine-tuning, voice selection, and design in making AI sound human
- How global brands use multilingual AI to deliver support that feels "local" everywhere
Key takeaways
- True multilingual AI goes beyond translation: PolyAI’s new unified multilingual system lets enterprises build a single agent that can understand and respond naturally across dozens of languages — capturing cultural nuance, not just words.
- Raven sets a new standard for accuracy: Unlike general LLMs that can “slip” back into English mid-conversation, Raven maintains 99.9% language consistency and adapts tone, formality, and gender appropriately across languages.
- Cultural intelligence is the differentiator: From how names are “written” in Mandarin to the extra politeness needed in Japanese, PolyAI’s platform allows per-language style guides and voice tuning to create humanlike, culturally informed customer experiences.
- The future is speech-to-speech: With Raven iterations in development, PolyAI is training models that understand and respond directly to audio, improving latency and naturalness — moving closer to real-time, multilingual conversations without separate ASR pipelines.
Transcript
Jenn Cunningham
00:19 – 01:06
Hi, everyone. Thank you so much for joining deep learning with PolyAI.
We’re here to help CX leaders get a window into the latest and greatest developments in AI. So I’m your guest host, Jenn Cunningham.
I’ll be subbing in for Nicola today, to bring you insights from our PolyAI experts on multilingual capabilities and why they matter. So, obviously, it’s a podcast.
Have to encourage you to hit the subscribe button, give us a like on YouTube, or leave a five star rating in the podcast app. But with, without further ado, I’m gonna go ahead and hand it over to Matt and viola.
If you two could please introduce yourselves.
Matt Henderson
01:06 – 01:17
Hey. I’m Matt.
I’m a VP of research, at PolyAI and leading a team, that’s among other things training LLM. So excited to talk about about that today.
Yeah.
Jenn Cunningham
01:17 – 01:17
Fantastic.
Viola Lin
01:17 – 01:27
Yeah. Hi.
I’m viola. I’m the product manager of PolyAI.
I have been focusing on enabling multilingual capabilities on our agent.
Jenn Cunningham
01:27 – 03:19
Amazing. Thank you.
Thank you guys so much for being here. I’m so excited.
When. Kind of the idea for this podcast episode first came about, I thought it would be really great to talk about our multilingual capabilities because Matt, with Raven v three, we have these fantastic, new capabilities built into the LLM, but then, viola, you’ve also been working on all of these fantastic upgrades to agent studio, from a platform perspective.
So it seems only fitting that we really talk about multilingual solutions, especially now. So when we think about the history of PolyAI, our we’re called PolyAI because our founders were all polyglots.
And so it seems only fitting that we have a polyglot solution as well that can kind of support different languages. I recently got back from our Vox event, in San Diego, and the theme was fluent.
And so we were thinking about fluency as mastery, right, in terms of conversational AI. But there is just fluency in multiple languages, and being able to have a multilingual solution.
So I guess, Matt, viola, curious to get your thoughts on what does multilingual really mean in the world of voice AI. Matt, I guess maybe if we wanna start with you.