Personalized product discovery
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ASOS integrated Azure OpenAI Service and Azure AI prompt flow to build an AI-powered natural language interface on its website and mobile app for personalized product recommendations. They implemented the solution by connecting their existing microservices with these AI tools, streamlining rapid prototyping and integrating external trend data along with internal expertise to curate tailored selections that enhance customer engagement. The solution seamlessly integrates into ASOS’s digital processes.
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Prototype developed in weeks; validated with 150 internal tests showing zero safety issues
28
AI use cases in
Consumer Goods
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Mercari integrated OpenAI’s API with a multi-model approach to optimize product listings. Initially, GPT‑4 analyzed top listings offline while GPT‑3.5 Turbo provided real-time suggestions for active listings. Later, they shifted to GPT‑4o mini to automatically generate complete titles, descriptions, and category suggestions from uploaded photos, streamlining the seller listing workflow.
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Pets at Home built an AI agent using Microsoft Copilot Studio integrated into its unified Azure data platform that consolidates disparate systems from its retail stores, online channel, veterinary clinics, and grooming services. This agent empowers the retail fraud detection team by rapidly scanning extensive transaction data to identify anomalies such as duplicate images in fraudulent claims, thereby streamlining fraud investigations. The implementation required minimal coding and seamlessly connected existing systems while ensuring strict data privacy within the company ecosystem.
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Petbarn developed and integrated PetAI, a generative AI-powered intelligent assistant using Azure OpenAI Service, Azure AI Search, and Azure App Service. They implemented the solution through virtual discovery sessions and design workshops, followed by iterative development of a multi-agent retrieval augmented generation model to deliver highly personalized pet care advice and product recommendations. The system was deployed on both their website and mobile app, streamlining customer interactions and enhancing pet care guidance.
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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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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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