Lottoland Breaks Language Barriers with AI-Powered Service

Use case typeCustomer service automationUpdated 1 day ago

Lottoland is a world-leading lotto and gaming operator serving more than 21 million customers across 15 international markets. The company needed multilingual customer support that worked around the clock and reduced manual routing, handling times, and agent workload. Boxfusion and Lottoland built a Gen-AI Oracle chatbot integrated into Oracle Service, Agent Live Chat, and Incident Translation to provide multilingual self-service, real-time agent guidance, and automated data collection before escalation.

Organization: Lottoland
Industry: Consumer & Food
Location: IM
Published: July 2026

Reported outcomes

+38%

query deflectionAutomation & deflection

Strategic outcomes

Customer experience & trustImproved first-contact resolutionCost efficiencyReduced routing bottlenecks and workloadScale & capacityEnabled scalable 24/7 multilingual support

Catalog median for automation & deflection deployments: +68% across 125 reported metrics. Compare benchmarks →

Primary read

Use case focus

Showing 2 of 2

1Customer service automation
2Multilingual communication

Multilingual 24/7 support demand created bottlenecks and higher costs; non-English queries required manual routing, limiting availability; agents needed better contextual knowledge and faster resolution.

Built a Gen-AI Oracle chatbot integrated with Oracle Service, live chat, incident translation, and Confluence knowledge to detect language and intent, respond instantly, recommend actions to agents, and consolidate FAQs and SOPs into one knowledge hub.

Technologies

Oracle Digital Assistant Oracle Generative AI Oracle Service Confluence

38% query deflection with AI-generated responses; improved first-contact resolution and reduced routing bottlenecks, handling times, and agent workload across global markets; enabled a scalable, globally consistent 24/7 support model.

Architecture

A Gen-AI Oracle chatbot was integrated with Oracle Service, Agent Live Chat, Incident Translation, and Confluence knowledge sources to detect language and intent, provide multilingual self-service, recommend responses to live agents, and collect incident data before escalation.

Implementation partners1

Boxfusion Consulting

Sources & evidence1

Groundedness: 5/5Type: Case StudyPublished: Jul 12, 2026Publisher: Boxfusion ConsultingEvidence: PartnerConfidence: High

Primary source

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Customer evidence