SUCCESS STORIES
Food Delivery
+3,000 employees
Europe, Africa and Asia
239,581 total interactions supported
100+ languages presented
85% → 92% forecast accuracy improvement
Challenges
Supporting a multilingual operation at this scale creates significant complexity. Customers, couriers, and merchants may interact with the organization in different languages, while each interaction still needs to meet consistent operational and service standards.
The organization needed a scalable approach to multilingual customer experience that could support both high-volume languages and long-tail language requirements across multiple operational areas.
Key challenges included:
Supporting multilingual interactions across order delivery, courier acquisition and onboarding, and merchant management
Managing a highly diverse language landscape across multiple European markets
Maintaining consistent customer experiences across different languages and markets
Supporting both high-volume and lower-volume language requirements
Improving operational forecasting and adherence while scaling multilingual operations
Integrating AI-powered language capabilities into existing customer experience workflows
Solution
Graia powered by Mplus deployed AI-powered language capabilities to support multilingual interactions across the organization's operations.
The solution enabled the organization to manage interactions across a broad range of languages while creating a more scalable operating model for multilingual customer experience.
The deployment supported three key operational areas:
Order delivery support
Courier acquisition and onboarding
Merchant management
The solution included:
AI-powered language capabilities for multilingual customer interactions
Support for 100+ languages represented across the interaction data
480 language configurations across the operation
Coverage across both high-volume and long-tail language requirements
Support for major languages including English, Croatian, Bosnian, Romanian, Serbian, Georgian, Russian, Ukrainian, Moroccan, Tunisian, Nepali, Turkish, and Bulgarian with corresponding scripts.
Integration of AI language capabilities into existing customer experience workflows
Operational optimization to support improved forecasting, adherence, and SLA performance
By combining AI-powered language capabilities with operational expertise, Mplus helped create a unified approach to managing multilingual interactions across different customer and business groups.
Impact
The deployment expanded the organization's ability to deliver multilingual customer experiences at scale while contributing to measurable improvements in operational performance.
Across the measured period, the solution supported 239,581 interactions across 480 language configurations, with more than 100 languages represented.
Key outcomes included:
239,581 multilingual interactions supported
100+ languages represented across the interaction data
Forecast accuracy improved from 85% to 92%
8% adherence achieved across the operation
4% improvement in SLA compliance
Multilingual AI capabilities supporting order delivery, courier acquisition and onboarding, and merchant management
A scalable operating model supporting both core and long-tail language requirements
Greater flexibility to deliver consistent customer experiences across diverse European markets
Mplus supported the organization address the complexity of multilingual customer experience by combining Graia AI-powered language capabilities with operational expertise.
Rather than treating language coverage as a collection of separate market-level requirements, Mplus enabled a scalable approach in which AI could support interactions across a highly diverse language landscape while also contributing to broader operational performance.
The result is a multilingual customer experience model designed for scale — supporting hundreds of thousands of interactions across more than 100 languages while serving customers, couriers, and merchants across multiple operational areas.
By bringing AI-powered language capabilities into existing customer experience workflows, the company can create a more adaptable foundation for multilingual CX, while improving forecasting accuracy, adherence, and SLA performance.
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