Case studies

HealthTech · Events and conversational AI

An avatar that answers the visitor questions a help desk cannot keep up with

At XPOMET Medicinale 2024 in Leipzig we deployed Paula, a voice-activated AI avatar that handled visitor questions, navigation and exhibitor recommendations in real time. Built together with Johannesstift Diakonie, Paula took over what would otherwise need dedicated information staff, in a noisy, high-traffic conference environment.

Key results

2 langs
English and German detected automatically, switchable mid-conversation
Live
Real-time voice interaction in a noisy conference hall
Local
Wake-word detection on the device, nothing sent to the cloud
Web + DB
Live web search alongside the event database

Client: Johannesstift Diakonie
Johannesstift Diakonie Services GmbH, at XPOMET Medicinale 2024 in Leipzig, one of Europe’s leading healthcare innovation conferences.

Johannesstift Diakonie
Industry
HealthTech and events
Use case
AI avatar for visitor guidance
AI approach
LLM with speech and function calling
Languages
English and German, detected automatically
Environment
Live conference, high noise
Partner
Johannesstift Diakonie

In short

What an information desk cannot do at peak hour

  • XPOMET Medicinale brings dozens of exhibitors, a packed presentation schedule and an international audience into one crowded, noisy hall.
  • Finding a booth, checking a session time or asking about a company traditionally means a staffed help desk, which is expensive, uneven, and does not scale when everyone arrives at once.
  • Paula takes the question out loud, in English or German, and answers from the full event database with exhibitor details, programme and booth locations.
  • She activates on “Hallo Paula” with wake-word detection running on the device, shows the relevant exhibitor logos on screen, and can search the live web for anything outside the programme.

The starting point

The challenge

Build an interactive assistant that handles visitor questions in real time, in more than one language, in a live conference setting, and replaces the need for manual information desk staffing.

XPOMET Medicinale is a large healthcare innovation conference with dozens of exhibitors, a packed presentation schedule and a diverse international audience. Attendees have to find specific booths, check schedules and get information about companies and sessions, all while moving through a noisy, crowded space.

Traditionally that requires dedicated staff at help desks, people who know the full event schedule, the exhibitor details and the venue layout. Staffing it is expensive, inconsistent, and it does not scale to peak traffic when everyone arrives at once or a session changes.

The brief was to replace that with something a visitor can simply talk to.

The build

What we built

We built and deployed Paula, a voice-activated AI avatar stationed in the Pauls Health Area. Not a chatbot on a screen: a conversational system that holds a spoken dialogue with a visitor.

01

She works out which language you are speaking

Paula detects whether a visitor is speaking English or German and answers in that language, with no manual selection. A visitor can switch languages in the middle of a conversation and she follows.

02

Wake word processed on the device

A conversation starts with “Hallo Paula”. The wake-word model runs locally on the device, so no audio goes to the cloud just to activate her. She also notices when a conversation has ended and deactivates by herself.

03

The event database, reachable by question

Paula has access to the full event database: exhibitor details, the conference programme, session times and booth locations. Through LLM function calling she answers specific questions like “which companies are presenting on digital pathology” and recommends sessions based on what a visitor says they are interested in.

04

The screen follows the conversation

While she talks, Paula reads the visitor’s intent and puts the relevant exhibitor logos and details on screen. That turns a voice exchange into visual navigation, which is what someone standing in a hall actually needs.

05

Live web search for everything else

Beyond the event, Paula answers general questions using live web search, from the local weather to a factual question, which makes her useful outside conference logistics too.

An avatar that answers the visitor questions a help desk cannot keep up with

What changed

The results

Before

Visitor guidance handled by information desk staff. Limited capacity at peak hours, one language at a time, and no personal recommendations.

After

An avatar handling visitor questions in two languages with no queue, personal exhibitor recommendations, visual navigation, and no dependency on staffing levels.

Paula handled visitor interactions throughout the event and gave consistent, accurate information regardless of how busy the floor was. Nobody waited in line or searched a printed programme.

The multilingual capability was particularly well received by the international audience, which is the part a single-language help desk cannot cover.

For exhibitors she worked as an additional discovery channel, sending visitors to relevant booths and sessions based on what they had said they were looking for.

The deployment also showed that a conversational avatar holds up in real conditions rather than a quiet demo room: noise, crowds and unpredictable behaviour.

Questions about this project

AI avatar for visitor guidance. Build an interactive assistant that handles visitor questions in real time, in more than one language, in a live conference setting, and replaces the need for manual information desk staffing.

English and German detected automatically, switchable mid-conversation: 2 langs. Real-time voice interaction in a noisy conference hall: Live. Wake-word detection on the device, nothing sent to the cloud: Local. Live web search alongside the event database: Web + DB.

LLM with speech and function calling. Technology used: Large Language Models, Speech-to-text, Text-to-speech, Function calling, Local wake-word detection, Automatic language detection, Real-time web search, AI avatar.

Technology used

Large Language Models Speech-to-text Text-to-speech Function calling Local wake-word detection Automatic language detection Real-time web search AI avatar

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