VUX World

The contact centre holds a record of almost every customer interaction. Every conversation carries a signal about why customers are calling and what is behind it. Processing those conversations at scale took the power the contact centre never had before.
Ping Wu, CEO of Cresta, joins us to work through what that shift means for enterprise contact centres, from cutting the calls that should never happen to automating the ones that can be.
We get into how AI changed what a contact centre can see. Every call, every screen, every exchange can now be processed rather than sampled. Human effort never scaled the way silicon does, so for years most of that record went unread. Large language models bring processing power and language understanding to work through millions of conversations, see what is driving them and turn that into insight, coaching and automation.

Show notes

Follow Ping on LinkedIn: ⁠https://www.linkedin.com/in/pingwu
Learn more about Cresta: https://cresta.com
Download Cresta's CX Workforce Report: https://cresta.com/report/cx-workforce
Register for our webinar - Meet contact centre 3.0. The playbook you're using is obsolete: vux.ai/3.0

Follow Kane on LinkedIn: ⁠⁠⁠⁠⁠⁠⁠https://www.linkedin.com/in/kanesimms⁠⁠⁠⁠⁠⁠⁠
Find out more about VUX: ⁠https://vux.ai⁠⁠⁠
Subscribe to VUX World: ⁠⁠⁠⁠⁠⁠⁠⁠https://vuxworld.typeform.com/to/Qlo5aaeW?utm_source=podcast&utm_medium=audio⁠⁠⁠⁠⁠⁠
Subscribe to The AI Ultimatum Substack: ⁠⁠⁠⁠⁠⁠⁠⁠https://open.substack.com/pub/kanesimms⁠

Voice AI is the channel everyone is talking about in 2026. One of the biggest things slowing it down is often already sitting inside your stack.
In this episode, I’m joined by Endre Davids from Seamly to explore what really happens when businesses take an existing chatbot and move it into the voice channel.
We discuss why latency often starts deeper in the conversational platform than teams expect. Endre explains how companies can spend time optimising speech recognition and text-to-speech while the chatbot itself is responsible for much bigger delays.
The conversation gets into why voice needs a different interaction model, because people speak differently from how they type. That puts far more pressure on getting the conversation design right.
We also cover how to manage perceived latency, when it makes sense to reuse existing chatbot infrastructure and how sentiment, multimodality and customer context could shape richer voice experiences.
Endre and I keep landing on the same point. The success of voice AI depends heavily on conversation design, and voice punishes the shortcuts that chat lets you get away with.

Show notes

Follow Endre on LinkedIn: https://www.linkedin.com/in/endredavids
Learn more about Seamly: https://seamly.ai

Conversational Conference 2026: https://events.frankwatching.com/conversationalconference
Follow Kane on LinkedIn: ⁠⁠⁠⁠⁠⁠https://www.linkedin.com/in/kanesimms⁠⁠⁠⁠⁠⁠

Find out more about VUX: https://vux.ai⁠⁠
Subscribe to VUX World: ⁠⁠⁠⁠⁠⁠⁠https://vuxworld.typeform.com/to/Qlo5aaeW?utm_source=podcast&utm_medium=audio⁠⁠⁠⁠⁠
Subscribe to The AI Ultimatum Substack: ⁠⁠⁠⁠⁠⁠⁠https://open.substack.com/pub/kanesimms⁠

I'm joined by Cobus Greyling, AI evangelist at Kore.ai, for a wide-ranging conversation on where enterprise AI actually stands today.
We explore why many of the ideas now being presented as breakthroughs, from graph engineering and orchestration to intent detection and state management, have deep roots in conversational AI. 
We also get into one of the biggest barriers to enterprise AI adoption: data. We highlight why customer experience could become the entry point for much wider organisational transformation. We touch on how forward-deployed engineers could help businesses navigate that change and why security will become increasingly important as AI agents gain access to more systems and information.
I close with a buzzword bingo round for Cobus covering fleet engineering, agent swarms, orchestration and universal agents, and Cobus explains why he thinks Open Claw was the biggest red herring of the year.

Show notes

Follow Cobus on LinkedIn: https://www.linkedin.com/in/cobusgreyling
Cobus's website: https://cobusgreyling.me
Follow Cobus on Substack: https://cobusgreyling.substack.com/
Discover more about Kore.ai
Article - The Untrainable by Sarah Guo: https://saranormous.substack.com/p/the-untrainable
Video - Andrej Karpathy: Software Is Changing (Again): https://www.youtube.com/watch?v=LCEmiRjPEtQ

Follow Kane on LinkedIn:
⁠⁠⁠⁠⁠⁠https://www.linkedin.com/in/kanesimms⁠⁠⁠⁠⁠⁠

Find out more about VUX:
⁠⁠https://vux.ai⁠⁠
Subscribe to VUX World: ⁠⁠⁠⁠⁠⁠⁠https://vuxworld.typeform.com/to/Qlo5aaeW?utm_source=podcast&utm_medium=audio⁠⁠⁠⁠⁠
Subscribe to The AI Ultimatum Substack: ⁠⁠⁠⁠⁠⁠⁠https://open.substack.com/pub/kanesimms⁠

Plenty of AI assistants can answer the question in front of them. Fewer can work out what someone is actually trying to do and help them do it.
In this episode, we're joined by Pete Kowalczyk, AI Conversation Designer at the Government Digital Service (GDS), to talk about designing AI experiences across the vast and complex landscape of UK government services.
Pete explains how GDS is exploring knowledge graphs, persistent state and goal detection to move beyond basic RAG systems. The aim is to connect information with action and guide people through non-linear journeys, such as moving house or registering a birth. One of the key goals is to reduce the burden created by fragmented processes and legacy systems.
We discuss why conversational systems need to track user goals, how small interaction loops can be built into rich experiences over time and why transitions between stages of a conversation carry so much weight for trust and usability.
We also get into progressive disclosure, deciding when an AI should stay concise and when it should offer more, and how to judge whether a link belongs in a response at all. Pete points to a bank surfacing patterns in someone's spending as an example of how organisations can build proactive features from data they already hold, rather than only responding when asked.
Pete shares how the designer role is evolving. Designers now need sufficient technical understanding to prototype and work directly with LLMs through practices like vibe coding, while maintaining the creative ability to understand experiences beyond incremental chatbot improvements.
He closes with a warning against the industry's current resolution rut, where success gets defined too narrowly as fast ticket resolution rather than genuinely useful, proactive AI.

Show notes

Follow Pete on LinkedIn:
⁠https://www.linkedin.com/in/petekowalczyk
Video of Pete's talk at the Conversational AI Meetup in London: ⁠https://youtu.be/001PeZv3N0k⁠
Lead with Tempo 2026: https://www.leadwithtempo.com/2026schedule
London Design Festival: https://londondesignfestival.com

Follow Kane on LinkedIn:
⁠⁠⁠⁠⁠https://www.linkedin.com/in/kanesimms⁠⁠⁠⁠⁠

Find out more about VUX:
⁠https://vux.ai⁠
Subscribe to VUX World: ⁠⁠⁠⁠⁠⁠https://vuxworld.typeform.com/to/Qlo5aaeW?utm_source=podcast&utm_medium=audio⁠⁠⁠⁠
Subscribe to The AI Ultimatum Substack: ⁠⁠⁠⁠⁠⁠https://open.substack.com/pub/kanesimms⁠

Almost a third of Simplyhealth's incoming calls are now resolved by AI, and email handling time has fallen from 12 minutes to 2. The company is achieving those gains while maintaining the service standards that placed it 31st in KPMG UK's Customer Experience Excellence report.
In this episode, we're joined by Paul Atkins, Head of Business Optimisation at Simplyhealth, the UK's member-owned health cash plan provider serving around 2.5 million customers. Paul explains how Simplyhealth introduced voice AI gradually, tested more than 1,000 real customer calls and built trust across a highly regulated organisation.
We also get into how Simplyhealth measures resolution, quality and customer effort, why intensive human listening still matters during rollout, and the organisational call to define what "good enough" looks like rather than letting advisors over-engineer every reply. Paul talks through the role of business readiness teams in driving adoption and why knowledge management could become the next major challenge in making AI work at scale.

Show notes

Follow Paul on LinkedIn:
https://www.linkedin.com/in/paul-atkins-1nsight
Follow Kane on LinkedIn:
⁠⁠⁠⁠https://www.linkedin.com/in/kanesimms⁠⁠⁠⁠

Find out more about VUX:
https://vux.ai
Subscribe to VUX World: ⁠⁠⁠⁠⁠https://vuxworld.typeform.com/to/Qlo5aaeW?utm_source=podcast&utm_medium=audio⁠⁠⁠
Subscribe to The AI Ultimatum Substack: ⁠⁠⁠⁠⁠https://open.substack.com/pub/kanesimms⁠