Timely tutor support
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Universitas Terbuka implemented an AI tutor by integrating Azure OpenAI Service and Azure AI Foundry within its customized Moodle LMS. The solution involved indexing course materials and grading rubrics using Azure AI Document Intelligence, employing Azure AI Vision for OCR-based assessments, and deploying through a scalable microservices architecture using AKS and Azure App Service. This integration streamlined student assessments and reduced educator workload by automating repetitive queries.
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Expanded to 100,000 students across 500 classes; assignment turnaround reduced from days to 1-2 days; improved student engagement and assignment scores in pilot data.
43
AI use cases in
Education
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Pensieve integrated Anthropic's Claude models (Claude 3.5 Sonnet and Claude 3.7 Sonnet) to build AI teaching assistants that automate grading and provide 24/7 personalized tutoring. The system clusters student submissions to calibrate grading rubrics and transforms static PDFs into interactive worksheets while enforcing instructor-controlled policies. This integration streamlines course management workflows and enhances real‐time classroom analytics.
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Super Teacher integrated Anthropic's Claude to generate initial code for interactive educational tools and draft lesson plans for subjects ranging from pre-K to 5th grade. They embedded the AI into both software development and content creation workflows with mandatory human review to ensure safety and quality standards. This integration streamlined operational processes, enabling engineering and content teams to focus on higher-level development and creative enhancements.
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Praxis AI integrated Anthropic's Claude 3.5 Sonnet via Amazon Bedrock to create AI-powered digital twins of professors that serve as virtual teaching assistants. They implemented this by switching from GPT-4 to Claude using an LLM switcher and deploying the solution on a secure, scalable AWS infrastructure that supports multi-agent workflows and real-time conversational features. This approach enhanced round-the-clock personalized student engagement and alleviated faculty workload.
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166
companies using
Customer Agents
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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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Zendesk integrated OpenAI's models to create adaptive AI service agents that autonomously manage customer conversations and execute resolution tasks. They implemented a multi-agent architecture featuring task identification, conversational RAG, procedure compilation, and procedure execution agents integrated with existing support workflows through API calls and natural language procedure definitions, while providing real-time chain-of-thought visibility. This solution transitions from traditional intent-based bots to a hybrid model of scripted and generative reasoning, streamlining customer service processes.
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Hebbia built Matrix, a multi-agent AI platform that orchestrates OpenAI models including o3‑mini, o1, and GPT‑4o to automate complex financial and legal research tasks. The platform decomposes intricate queries into structured analytical steps and integrates modules like OCR, hallucination validation, and artifact generation to process complete documents, creating an infinite effective context window. This solution streamlines due diligence, contract review, and market research workflows, drastically reducing manual processing time.
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226
solutions powered by
Microsoft
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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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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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Ontada leveraged Microsoft’s Azure OpenAI Service Batch API and Azure AI Foundry to build its ON.Genuity platform, which processes 150 million unstructured oncology documents to automatically extract nearly 100 critical data elements across 39 cancer types. They integrated the new platform with their structured iKnowMed system using Azure Databricks for data ingestion and Azure Document Intelligence for text extraction, transforming manual chart review processes into an automated workflow that supports clinical decision-making and life science product development.
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59
AI use cases in
Asia
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LY Corporation leveraged OpenAI’s API to integrate advanced generative AI into its flagship services, including a GPT‑4o-powered LINE AI Assistant and GPT‑4 enhancements in Yahoo! JAPAN Search for summarizing reviews and generating travel plans. They also deployed SeekAI, an in-house productivity tool using RAG to rapidly retrieve information from internal documentation, streamlining employee inquiries and operations.
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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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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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