VUX World

What happens when customers stop opening banking apps and start managing their finances through AI assistants?In this episode, we sit down with Mathias Fanschek, Head of Digital Transformation and Retail Strategy at Raiffeisen Bank International, to explore how one of Europe's largest banking groups is preparing for a future of headless banking, agentic commerce and AI-powered customer experiences.With 18 million customers across 11 markets and managing over €200 billion in assets, Mathias shares what it really takes to move generative AI from experimentation to production. We had a good discussion about virtual mobile assistants, transforming legacy data infrastructure, and managing executive expectations in a rapidly changing, highly regulated landscape.You'll also hear Mathias' perspective on Revolut's new PRAGMA model, why context is the missing ingredient in today's AI experiences and how banks can remain trusted intermediaries as customers increasingly interact through AI-powered distribution channels.

We sit down with Henry Vaage Iversen, Co-Founder and CCO at boost.ai, to explore why voice AI is finally reaching mainstream deployment across banks, insurers, telcos and other regulated industries.We dig into what's changed in the technology, why phone volumes continue to rise and how large language models are reshaping what's possible on the voice channel. Henry shares practical lessons from deploying conversational AI at scale, including how some customers are now achieving 60-75% voice automation. We also discuss why the gap between chat and voice experiences still catches companies off guard, and what it really takes to get voice AI right in terms of testing, latency, and conversation design.We explore why layering AI onto legacy channels only gets you so far, and why the real opportunity lies in rethinking customer journeys from scratch. The conversation wraps with a story about what happens when AI agents start calling other AI agents, something our team recently experienced firsthand.Show notesFind out more about boost.aiFollow Henry on LinkedInTake our updated AI Maturity AssessmentSubscribe to our newsletterSubscribe to The AI Ultimatum Substack

Five years after his ⁠first appearance on the podcast⁠, PolyAI CEO Nikola Mrkšić returns to VUX World to discuss how conversational AI has evolved from intent-based systems into enterprise-scale AI agents handling millions of customer interactions.PolyAI began as a research-led spinout from Cambridge University with a singular focus on making automated voice conversations genuinely useful. Since then, the company has grown from a handful of pilot deployments to powering customer service operations for nearly 200 enterprises worldwide, including highly regulated industries such as banking, healthcare, insurance and utilities.In this episode, we explore what it actually takes to build production-ready conversational AI systems at scale. We go deep into PolyAI's proprietary Raven model, the realities of building and training purpose-built language models for enterprise customer service. We also talk about why most businesses underestimate the complexity of deploying AI agents into real-world operations.The conversation also touches on PolyAI's brand campaign starring Gordon Ramsay. Ramsay's restaurants have been a PolyAI client for a few years, and the company launched a campaign timed to the Super Bowl in February 2026 with Ramsay dramatising the contrast between legacy phone menus and PolyAI's voice agents. Nikola explains how the partnership came about and why Ramsay's standards made him a fitting brand ambassador for the company.Show notes Find out more about PolyAI: ⁠https://poly.ai/⁠Follow Nikola on LinkedIn: ⁠https://www.linkedin.com/in/nikola-mrksic⁠ Follow Kane on LinkedIn: ⁠https://www.linkedin.com/in/kanesimms⁠Sign up for our upcoming webinar - Cutting headcount isn't an AI strategy: ⁠https://events.vux.ai/getvocal?utm_source=podcast_network&utm_medium=podcast⁠  Take our updated AI Maturity Assessment: ⁠https://vuxworld.typeform.com/to/a26bf9Rr?utm_source=podcast_network&utm_medium=audio⁠Subscribe to our newsletter: ⁠https://vuxworld.typeform.com/to/Qlo5aaeW/?utm_source=podcast_network&utm_medium=podcast⁠ Subscribe to The AI Ultimatum Substack: ⁠https://open.substack.com/pub/kanesimms

Enterprise AI projects fail more often than they succeed. The MIT figure Thomas Schaefer cites puts that at 95%. The reasons are rarely the model. They are the architecture beneath it, the data that feeds it, and the use case selection that determines whether any of it was worth starting.Thomas Schaefer is Director of Sales Engineering at Uniphore, based in Germany. He has over 20 years in enterprise technology, including 12 years at Jacada across solution architecture, professional services and presales leadership across EMEA and APAC. He joined Uniphore in 2021 and works with enterprise clients on AI transformation, agentic workflow design and the operationalisation of business AI at scale.Show notesDiscover more about the CCW UK Summit: https://europe.customercontactweekdig...Find out more about Uniphore: https://www.uniphore.com/Follow Thomas on LinkedIn: https://www.linkedin.com/in/thomas-schaefer-4027a611/Follow Kane on LinkedIn: / kanesimms Take our updated AI Maturity Assessment: https://vuxworld.typeform.com/to/a26b...Subscribe to VUX World: https://vuxworld.typeform.com/to/Qlo5...Subscribe to The AI Ultimatum Substack: https://open.substack.com/pub/kanesimms Hosted on Acast. See acast.com/privacy for more information.

Enterprise AI tools can spin up a prototype in an hour. Getting that prototype to production with the accuracy, security, and scale a real business needs still takes months for most companies. Inbenta says its new Encore platform closes that gap in days or even hours.Merlin Bise, CTO at Inbenta, returns to VUX World to walk through how Encore builds production-grade AI agents on the fly when a customer deploys a use case. The platform ingests content from websites, documents, recordings and connected systems like SharePoint, then combines large language models with Inbenta's proprietary NLP, customer-specific lexicons and real-time intent generation to deliver near-zero hallucination rates.The hallucination numbers from raw models remain striking. We discuss a report that shows hallucination rates across different LLMs, including those from companies such as OpenAI, Google, and xAI. Inbenta's approach constrains the model to verified content and context, then layers intent-based NLP on top. In one customer test of 200 questions, they found a single hallucination, caused by a query that fell outside the content boundaries. We also discuss the broader trajectory of enterprise AI. Most deployments today focus on replacing existing activities or functions. The bigger opportunity lies in using AI to imagine entirely new kinds of value. Merlin predicts that hyper-automation, which combines agentic intelligence with robotic process automation, will be the defining shift in the next 12 months.Show notesFind out more about The European Chatbot & Conversational AI Summit: https://europe.customercontactweekdigital.com/events-ccw-uk/agenda-mc/?utm_source=VUX%20World&utm_medium=Media%20Partner&utm_campaign=47758.003_VUX_Social_Post_Agenda&utm_term=&utm_content=&disc=&extTreatId=7634824Find out more about Inbenta: https://www.inbenta.comFollow Merlin on LinkedIn: https://www.linkedin.com/in/merlin-bise-8277696bFollow Kane on LinkedIn: https://www.linkedin.com/in/kanesimmsTake our updated AI Maturity Assessment: https://vuxworld.typeform.com/to/a26bf9Rr?utm_source=podcast&utm_medium=audioSubscribe to VUX World: https://vuxworld.typeform.com/to/Qlo5aaeWSubscribe to The AI Ultimatum Substack: https://open.substack.com/pub/kanesimms Hosted on Acast. See acast.com/privacy for more information.