Government & Public SectorConversational AI

Munich Fire Department tests an AI operator for non-emergency patient transport calls, built on Microsoft Foundry

Munich Fire DepartmentMicrosoft Foundry · Azure Speech · Azure AI Search

The Munich Fire Department and Microsoft built a multilingual voice AI operator to take non-emergency patient transport calls from hospitals and nursing homes, using Microsoft Foundry, Azure Speech and Azure AI Search to validate addresses against a municipal database. Human dispatchers stay in the loop and calls hand off to them when the bot does not understand. In beta testing, with broader testing planned at LMU Klinikum.

Overview

The Munich Fire Department and Microsoft built a multilingual voice AI operator to take non-emergency patient transport calls from hospitals and nursing homes, using Microsoft Foundry, Azure Speech and Azure AI Search to validate addresses against a municipal database. Human dispatchers stay in the loop and calls hand off to them when the bot does not understand. In beta testing, with broader testing planned at LMU Klinikum.

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The challenge

Munich Fire Department dispatchers handle emergency calls and also arrange non-emergency patient transports between hospitals or home from nursing homes. The department wanted to relieve pressure on dispatchers, shorten waiting times for hospitals and nursing homes that book transports, and ease the process for health-care workers, many of whom speak German as a second or third language.

The solution

IT experts from the fire department and Microsoft built an AI operator that handles non-emergency transport calls in natural language in several languages. Microsoft Foundry assembles and governs the chatbot, Azure Speech (HD Voice) supplies the voice, and Azure AI Search validates addresses against a municipal database. A human dispatcher takes over immediately if the chatbot does not understand something.

Conversational AISpeech & Audio AI

Reported business value

The source reports no measured results. In beta testing, testers have said the AI operator has been very effective and easy to use. The department hopes it can unburden dispatchers of non-emergency calls so they have more time for medical emergencies and fires, and a hospital emergency-ward director hopes it will save nurses' time and could help open hospital beds more quickly by cutting waiting times.

Sources

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This record was researched and written with AI assistance, and its claims were checked against the sources above. (EU AI Act art. 50 transparency notice.)

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