Deep Learning with PolyAI

An agent that gets better every day compounds into a very different agent within months. That's the idea behind Wren, PolyAI's new release: an agent whose job is to make your other agents better. Some of what it finds is a small refinement, some of it is a big fix. Either way, Wren watches every real customer conversation, learns from what happens, and keeps improving your customer-facing agents. Nikola Mrkšić sits down with Arkadiusz Kwapiszewski, Head of Agent OS, to get into what tha...

Companies are pouring money into AI, but not everyone is getting the returns. Ian Jacobs, VP and Lead Analyst at Opus Research, thinks he knows why. In this episode, your host Nikola Mrkšić sits down with Ian to work through two ideas from his latest research. The first is Conversation Experience Orchestration: the wall between conversational AI and conversation intelligence is coming down, and conversations are becoming the layer that decides what happens next. The second is the ...

When PolyAI built its Builder MCP, one client helped shape it: Vixxo Facility Solutions, one of the largest facilities providers in the US. In this episode, guest host Damian Sasso talks with Vixxo's CTO Derek Neighbors and VP of IT Bobby Hunnicut about getting AI agents into the hands of people who've never written code, from accounting to technicians in the field. They cover why an MCP or CLI has become their litmus test for adopting any technology, how they build and ship their own MCPs as...

PolyAI just launched Dialog-RSN-1, its first audio-native model, and your host Nikola Mrkšić sat down with its builder, Matt Henderson, to unpack why it’s a game-changer for building voice agents. Most voice AI either flattens a call into a transcript and loses the audio, or goes fully speech-to-speech and gives up control of the voice. Dialog-RSN-1 does neither. It hears the raw audio directly, decides when to speak, and keeps text-to-speech separate so the voice stays under your control, ...

Voice AI vendors love to quote word error rate, usually somewhere around 2 to 3%, as proof their system understands customers. Oliver Shoulson, Agent Design & Engineering Lead at PolyAI, thinks it's one of the most misleading numbers in the business. He and Nikola Mrkšić go through a month of analysis across more than 100,000 real production call turns to explain why. Turns out not all words carry the same weight, most transcription errors are harmless, and task success barely moves...