Faster customer issue resolution
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Vodafone uses Azure OpenAI Service, Azure AI Foundry, Microsoft Copilot, and Azure AI Search to enhance their virtual assistant TOBi and develop SuperAgent to assist customer service agents. TOBi uses conversational AI to handle customer inquiries, while SuperAgent helps agents solve complex problems faster.
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Fully resolves 70% of customer inquiries, reduced call times by at least one minute, increased customer satisfaction scores.
17
AI use cases in
Telecommunications
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SK Telecom integrated Anthropic's Claude on the Amazon Bedrock platform to power both in-call assist and post-call processing solutions. They implemented a custom in-house RAG model combined with real-time document search and automated summarization, classification, and sentiment analysis to augment call center operations and support culturally nuanced customer interactions.
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Wrtn Technologies leveraged Microsoft's Azure OpenAI Service with its newest o1 models to power a localized AI superapp, integrating features such as intelligent search, conversational chat, and code generation into its platform. They implemented the solution by incorporating Azure AI Foundry and Azure AI Content Safety to ensure secure data residency and regulatory compliance, streamlining both consumer interactions and internal development workflows.
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Bell Canada has built customizable contact center solutions for its business customers that offer AI-powered agents to address callers, and Agent Assist, which listens when a human agent is on, offering suggestions and sentiment analysis.
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172
companies using
Customer Agents
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NVIDIA partnered with Google Cloud to enable on-premises agentic AI by integrating Google Gemini models with NVIDIA Blackwell platforms and Confidential Computing, ensuring data sovereignty and regulatory compliance for sensitive enterprise operations. The solution further optimizes AI inference and observability by deploying a GKE Inference Gateway alongside NVIDIA Triton Inference Server, NVIDIA NeMo Guardrails, and NVIDIA Dynamo to enhance secure routing and load balancing for enterprise workloads.
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Intuit integrated Google Cloud’s Document AI and Gemini models into its GenOS platform to automate the autofill of ten common U.S. tax forms, including complex 1099 and 1040 forms. The solution extracts and categorizes data from uploaded documents, drastically reducing manual data entry for TurboTax customers. This integration streamlines tax preparation workflows and improves speed and accuracy.
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Capgemini partnered with Google Cloud to develop industry-specific agentic AI solutions that automate customer request handling across multiple channels such as web, social, and phone. The implementation integrates Google Agentspace, Customer Engagement Suite, and Agent2Agent interoperability protocol into existing customer service infrastructures to enhance personalized support, call routing, and workflow automation. This advanced solution transforms customer experience by streamlining communications and enabling proactive engagement.
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251
solutions powered by
Microsoft
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Physics Wallah developed 'Gyan Guru', a hyperpersonalized conversational study companion to address the unique academic and support needs of its 2 million daily users. The system was implemented by indexing over one million Q&As and ten million solved doubts in a vector database, then leveraging a Retrieval-Augmented Generation (RAG) approach integrated with Azure OpenAI to deliver individualized, context-aware responses. This integration streamlined various student interactions including academic queries, product-related issues, and general support, reducing reliance on human subject matter experts.
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Brandix adopted the Microsoft 365 Copilot suite via the Early Access Program to integrate AI into key executive workflows, automating meeting transcript-based action tracking in Teams, accelerating pitch deck creation in PowerPoint, and streamlining document generation in Word while leveraging AI-enhanced querying in Power BI and efficient information retrieval via Copilot Chat. This implementation transformed internal communications, reporting, and presentation preparation processes by significantly reducing manual effort.
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University of Oxford’s IT Services department deployed Microsoft 365 Copilot across its 400+ staff as part of a pilot program aimed at embedding generative AI into research, teaching, and administrative workflows. They implemented extensive onboarding sessions, community engagement via Microsoft Teams, and established an acceleration team to integrate Copilot with other business applications. This deployment streamlined routine tasks such as document generation, summarization, and meeting support, fostering innovation within the department.
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159
AI use cases in
Europe
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Deutsche Bank developed DB Lumina, an AI-powered research agent built on Gemini and Vertex AI through a partnership with Google Cloud. The solution automates the creation of financial research reports by rapidly condensing extensive market data—such as converting a 400-page report into a three-page summary—thereby streamlining analysis workflows while maintaining rigorous data privacy standards.
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Capgemini partnered with Google Cloud to develop industry-specific agentic AI solutions that automate customer request handling across multiple channels such as web, social, and phone. The implementation integrates Google Agentspace, Customer Engagement Suite, and Agent2Agent interoperability protocol into existing customer service infrastructures to enhance personalized support, call routing, and workflow automation. This advanced solution transforms customer experience by streamlining communications and enabling proactive engagement.
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wealthAPI implemented a next‐gen contract detection solution by integrating DataStax Astra DB on Google Cloud and leveraging Google Gemini models for AI‐powered analysis. They deployed DataStax’s vector search and real‐time insights capabilities to scale contract detection across millions of users in less than three months, streamlining wealth management workflows by dramatically reducing response times and efficiently handling massive data volumes.
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