AI, Operation and a LEGO F1 Car: What I Learned at HETT 2026

Written by Ian Perry, Senior Solutions Architect

Last week Cisilion exhibited at HETT for the first time. We were on Stand G1 at ExCeL London on 29 and 30 September, right by the entrance, between the NHS Feature and the AI Zone. That’s a good spot if you’re talking about AI in healthcare. I’ll admit there was some pressure when the AI Zone was a few steps away.

The numbers

Here’s what two days at HETT looked like for us:

• 3,000+ healthcare professionals came to HETT this year, according to the organisers
• 186 badges scanned at our stand across the two days
• At one point there was a queue for the demo. I’m taking that as a career highlight.

Put another way, about one in every 16 people at the show stopped at our stand long enough to have their badge scanned.

Listening first, then showing

What struck me most was who came to talk to us. Many visitors were clinicians, not just people from digital and IT teams. That was the best thing that could have happened. They told us what really goes on: phone lines that are always busy, receptionists who never stop, and clinicians who spend time on admin that could go to patients.

I had a few ideas for how AI could help with that, so I built them into a working demo. To make it look real, I made a pretend GP practice called Ecofriendly GP Surgery, with its own website, phone number and web chat. Behind it sat Webex Contact Center, a Webex AI Agent and a small patient database. We showed three scenarios:

1. “I’ve hurt my back.” A patient calls for advice. The AI Agent answers using its NHS knowledge source. When the patient asks to see someone, it picks a suitable clinician, books the appointment and sends an SMS confirmation. Nobody in the practice has to touch it.
2. “I can’t make my appointment.” A patient calls to cancel. The AI Agent confirms who they are and removes the appointment from the system. That frees the slot for someone else instead of it becoming another missed appointment.
3. “Can I get my test results?” The AI Agent isn’t allowed to talk about results, so it passes the call to a person. When the call reaches the clinician, the patient’s record opens on their screen, showing the latest test results and next appointment. The patient doesn’t have to explain everything again.

I also recorded all three as videos, because I wasn’t certain how good the exhibition WiFi would be and fully expected the hall to be too loud for a live voice demo. It’s good to plan for the worst. As it happens, the WiFi was pretty good, but it was certainly loud in there at times.

The demos weren’t really the point, though. What they did was start conversations. Visitors watched a call get handled, then said things like “we could do that for…” and told us about their own problems: outpatient bookings, call volumes in mental health services, discharge follow-ups. One ICB was already looking at AI scribing for GP practices. Another trust is merging with three others and needs help with access rights across all of them. That’s the conversation I wanted to have. The question moves from “what is AI?” to “where would AI save time and money for us?”

Patients, professionals and the network underneath

Our message came down to three things:

• Better patient experience. Patients get answers 24/7, appointments are handled without waiting in a queue, and when they need a person they don’t have to repeat themselves.
• More efficient professionals. The routine calls are handled automatically, and the clinician has the full picture on screen before saying hello.
• The infrastructure underneath it. None of this works without a network and connectivity you can rely on. Cisilion has been delivering that for years, and the stand made the point clearly: “Connected networks delivering better patient outcomes.” AI can only be as good as what it runs on. A few visitors wanted to start there, including one trust that asked about a network assessment.

Operation (no surgeon required)

Now for the fun part. Jenny Gjasta came up with a healthcare version of the game Operation. Instead of taking out the funny bone, players had to remove “healthcare pain points” as quickly as possible. The fastest time on the leaderboard won a LEGO® Mercedes-AMG F1 W14 E Performance set.

It drew a proper crowd. There was a lot of nervous concentration, some steady hands, and plenty of buzzing. The winner was Lucy Prigmore, a therapeutic radiographer. She isn’t a surgeon, which I suspect has caused some awkward conversations in a few theatre departments. But when your job is getting radiotherapy exactly where it needs to be, a pair of tweezers and a buzzer probably don’t scare you. Congratulations, Lucy. You now have about £200 of LEGO to build, which may be the hardest procedure of the lot.

The team

Events like this work because of the people on the stand. Thanks to Stacie Hill, Jenny Gjasta and the whole marketing team for organising everything and for all the creative ideas. Thanks to Alex Hooper for leading the strategic conversations around AI ready infrastructure, and to Lydia Smith, Abinash Bangar, Ryan Wells, Ben Porter-Goff and Shane Baker from the sales team for filling the meeting diary before and during the show.

What’s next

We’re now following up with every trust and ICB we spoke to. If we spoke at HETT, or if you’d like to see how AI could take pressure off your front door, get in touch. I’m happy to run the demo again. The WiFi will probably be better this time.