Use case type

Language translation

Language translation groups 3 documented AI deployments in the AI Use Case Hub. Adoption so far spans Public Sector and Tech & Comms. Browse the company examples below to see how teams put it into production.

Use cases

3

Examples

3

Industries

2

Timeline

2 mo

Company examples

Use cases of this type

3 shown from 3 use cases

MicrosoftMay 12, 2025

RhB Revolutionizes Rail Customer Service with Flurina Chatbot

RhB Rail Service collaborated with ParetoLabs to implement Flurina, an AI-powered chatbot using Azure OpenAI Services. Developed to address increasing customer queries amidst labor shortages, Flurina provides 24/7 assistance in multiple languages. Hosted securely on Swiss Azure data centers, it enhances customer satisfaction and complies with privacy regulations. The chatbot uses a tailored knowledge database and integrates fact-checking tools to deliver accurate and reliable information.

RhB Rail ServicesPublic Sector
GCPJan 1, 2024

Minnesota Department of Public Safety: Bidirectional real-time virtual agent translation for driver and vehicle services

The Minnesota Department of Public Safety’s Driver and Vehicle Services division improved access to driver’s license and ID services for residents who are not fluent in English. The organization addressed language barriers that previously required in-person translation assistance or bringing a translator to appointments.The implementation uses Google Cloud virtual agents with real-time translation to support chat, text, and form-based interactions on the DVS website, helping residents complete common self-service tasks in their preferred language.

Minnesota Department of Public SafetyPublic Sector
GCPDate unknown

Ateme Automates Multilingual Subtitling with Google Cloud Generative AI

Ateme automated the complex and time-consuming process of multilingual subtitle generation using Google Cloud's generative AI services, reducing subtitle creation time from 15 hours to minutes.The integration with Google Cloud's Vertex AI and Gemini models enables automatic audio transcription, timecode spotting, and subtitle generation in multiple languages, meeting broadcasters' accuracy expectations.Ateme leveraged a cloud-native architecture on Google Kubernetes Engine and Cloud Storage to build a scalable, fully integrated subtitling workflow.This innovation significantly lowers costs, enhances content accessibility including for disabilities, and helps clients comply with regulatory requirements.

AtemeTech & Comms
This website uses cookies to enhance the user experience. Learn more.