Faster asset mapping
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BMW Group, in collaboration with SORDI.ai and Monkeyway, deployed a generative AI system that scans a wide range of industrial assets and uses Vertex AI to produce detailed 3D digital twins. This automated solution replaces the slow, manual asset mapping process, enabling rapid simulation of multiple industrial scenarios to optimize planning and supply chain efficiency.
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13
AI use cases in
Automotive
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BMW Group implemented a cloud-based mobile data recorder (MDR) system by installing IoT devices in development cars to automatically capture and transmit extensive vehicular telemetry to Microsoft Azure. They built a comprehensive platform using Azure IoT Hub, Azure App Service, and Azure Kubernetes Service, and integrated Azure OpenAI Service with GPT-4o via Azure AI Foundry to create an MDR copilot that converts natural language queries into Kusto Query Language (KQL). This solution streamlined real-time data capture, analysis, and troubleshooting, accelerating vehicle prototyping and enhancing development quality.
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Localiza, a leading mobility company in Latin America, implemented Microsoft 365 Copilot to automate processes and improve efficiency. By integrating AI into their workflows, they enhanced employee productivity, optimized repetitive manual tasks, and improved inclusivity. They conducted training and hackathons to help employees effectively use Copilot, resulting in significant productivity gains across the company.
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Toyota deployed a system named O-Beya integrating nine specialized AI agents powered by GPT-4o to capture and consolidate decades of engineering expertise. The solution leverages Microsoft Azure OpenAI Service with API integration via Azure Functions and a vector search–enabled Cosmos DB to process design reports, regulatory data, and handwritten documents, streamlining powertrain design workflows and preserving expert knowledge amid retirements.
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149
companies using
Data Agents
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Aura Intelligence integrated Anthropic's Claude via Amazon Bedrock into its data pipeline to automatically classify over 200 million job titles and industry pairings from multi-language data, replacing manual lookups and fuzzy matching. They fine-tuned foundation models on proprietary datasets and leveraged AWS infrastructure, including SageMaker and prompt management, to automate QA, report generation, anomaly detection, and real-time hiring trend analysis.
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LaunchNotes leverages Claude in Amazon Bedrock in their product 'Graph' to transform engineering data into actionable insights. Graph functions as an ETL platform with Claude managing data pipelines, helping engineering managers understand development metrics, reduce incident identification time, automate updates, and generate customized release notes and technical documentation.
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Snowflake integrated Anthropic's Claude into their platform to enable natural language queries on complex databases, allowing customers to extract insights without SQL expertise while maintaining security and governance.
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255
solutions powered by
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704 Apps implemented an AI solution using Vertex AI and Gemini 1.5 Pro to automate and accelerate driver identity verification and safety monitoring. They integrated these AI models into their existing cloud infrastructure built on Firebase and Google Kubernetes Engine, centralizing real-time data for document validation and audio sentiment analysis. The system alerts the central monitoring team when risk-related language is detected, streamlining operational decision-making and enhancing security.
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OPPO integrated Google Cloud’s Vertex AI, AutoML, and Gemini large language model into its mobile devices to automate user feedback analysis, power AI Recording Summary features, and enable AI Toolbox functionalities such as AI Writer and AI Reply. They re-engineered their hardware platform, operating system, and third-party ecosystem to embed AI agents that optimize power consumption and reduce computing latency, streamlining mobile development workflows and enhancing user experience.
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Dataïads built an AI-powered “Post-Click Experience” system that automatically generates personalized landing pages by analyzing user context such as ad origin, product type, and behavior. The solution is implemented by integrating API access from Google Ads with Google Cloud managed services (Cloud Run and BigQuery) for automated scaling and controlled cost management, while planning to incorporate Vertex AI for further optimization. This implementation directly enhances ad campaign management and improves ecommerce conversion processes.
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153
AI use cases in
Europe
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Tidio integrated Anthropic’s Claude model to develop their Lyro AI agent, automating customer support interactions across both live chat and email channels. They implemented a network of specialized AI agents for conversation rating, summarization, and a dynamic routing system that selects the optimal API between native Anthropic API and Google Cloud Vertex AI based on performance metrics, streamlining support workflows and enabling personalized product recommendations.
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The school deployed Microsoft Reading Progress and Microsoft Immersive Reader, two AI-powered apps integrated within Microsoft Teams, to support individualized learning. The tools record reading sessions, provide real-time feedback on pronunciation and errors, and translate texts to enable comprehension across multiple languages. This setup streamlines classroom instruction, personalizes student learning, and reduces teacher workload.
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Dataïads built an AI-powered “Post-Click Experience” system that automatically generates personalized landing pages by analyzing user context such as ad origin, product type, and behavior. The solution is implemented by integrating API access from Google Ads with Google Cloud managed services (Cloud Run and BigQuery) for automated scaling and controlled cost management, while planning to incorporate Vertex AI for further optimization. This implementation directly enhances ad campaign management and improves ecommerce conversion processes.
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