AI use cases in Italy
6 documented implementations
Miroglio Group Unleashes Fashion Innovation in Italy with Generative AI on AWS
Miroglio Group
Italian fashion company Miroglio Group, which designs and distributes 10 fashion and lifestyle brands across 41 countries, worked with AWS Partner Data Reply to replace its manual product-tagging process with a generative AI-powered tagging system built on Amazon Bedrock using Anthropic's Claude 3.5 Sonnet, combined with a machine learning model trained on the company's historical images. The system analyzes product images and generates accurate technical and editorial tags and descriptions across multiple languages, reaching almost 90 percent accuracy and cutting a task that previously took one month down to about one hour.
Ferrari Advances Generative AI for Customer Personalization and Production Efficiency
Ferrari S.p.A.
Ferrari built a car configurator on AWS using LLMs in Amazon Bedrock and Amazon Personalize, letting customers personalize their vehicle across millions of possible configurations with 3D visualization, which increased sales leads and cut configuration times by 20%. Ferrari also fine-tuned Amazon Titan, Claude 3 and Llama models in Bedrock (combined with Amazon SageMaker JumpStart) on its own documentation to power an after-sales generative AI chatbot that classifies and summarizes customer care tickets, and uses Amazon Lookout for Vision to automate quality inspection and defect detection on the assembly line. Generative AI is also used to run vehicle design simulations and text-to-image prototyping to reduce reliance on physical prototypes.
Illimity modernizes commercial banking with Databricks and adopts LLMs for customer-centric chatbots
Illimity Bank
Illimity, an Italian digital bank, built its data architecture entirely around the Databricks Data + AI Platform to process data in real time, extract actionable insights and securely share it with partners. Databricks has supported Illimity's adoption of LLMs, using vector embedding and vector databases, to inform its knowledge base and power intelligent customer-centric chatbots. Illimity is also exploring Databricks Clean Rooms to monetize its architecture using deterministic or machine learning models without compromising confidentiality.
Unipol accelerates insurance operations with Generative AI built by Reply
Unipol Group
Italian insurer Unipol Group, serving customers through more than 2,000 agencies, worked with Reply (Cluster Reply and Sprint Reply) to build a governed Generative AI platform: a Foundation Layer/Unipol GenAI Stack using Azure AI Search and a Vector DB indexing over 60,000 documents; a Virtual Information Assistant chatbot with RAG over 50,000+ documents that reduces back-office ticket load and delivers responses in seconds; a network of AI agents built with Azure OpenAI, LangChain/LangGraph and UiPath that convert manual tasks into conversational interactions with real-time data validation; and an AI Guardrail governance layer (built on the LoopMind asset) providing LLM-as-a-judge monitoring, human-in-the-loop validation and AI Act compliance. Reply reports accelerated time-to-value, with new applications released in 1-3 months.
Fastweb + Vodafone: Transforming Customer Experience with AI Agents using LangGraph and LangSmith
Fastweb + Vodafone
Fastweb + Vodafone, part of the Swisscom Group and one of Europe's leading telecommunications providers serving millions of customers across Italy, built two AI agent systems on LangChain and LangGraph. Super TOBi transforms its existing chatbot TOBi into an agentic system using a Supervisor agent (for routing and guardrails) and specialized Use Case agents following the LLM Compiler pattern to call customer APIs and execute transactional actions like offer activation or payment updates. Currently serving nearly 9.5 million customers through the Customer Companion App and voice channels, Super TOBi achieves a 90% correctness rate, an 82% resolution rate, and a Customer Effort Score of 5.2 out of 7. Super Agent is an internal tool that augments call center consultants with diagnostics and guidance, storing operational knowledge as a graph in Neo4j and using an automated ETL pipeline with LangGraph and LLM agents to convert business-authored procedures into the knowledge graph; it has driven One-Call Resolution rates above 86%. The company uses LangSmith for observability, daily automated evaluation of chatbot responses, and continuous improvement.
Domyn builds Colosseum 355B, a sovereign AI foundation model, using NVIDIA DGX Cloud
Domyn
Domyn (formerly iGenius), an Italian AI company serving highly regulated sectors such as financial services and public administration, used NVIDIA DGX Cloud with over 3,000 NVIDIA H100 GPUs to continue-pretrain Colosseum 355B, a 355-billion-parameter foundation LLM. Within one week Domyn had access to the dedicated infrastructure, and within two months completed continued pretraining, achieving 82.04% accuracy on the MMLU benchmark. The model powers Domyn's business intelligence agent, Crystal, a sovereign AI solution deployed on private infrastructure.