Unipol accelerates insurance operations with Generative AI built by Reply
Unipol Group · Italy
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.
Overview
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.
The challenge
Unipol Group, one of the main players in the Italian insurance market, manages a high volume of requests every day through a network of over 2,000 agencies distributed across Italy. In an increasingly competitive and regulated context, Unipol needed to integrate Generative AI into insurance services safely and effectively, with the aim of transforming assistance for clients and agents, reducing ticket resolution times, and improving the experience for clients and employees.
The solution
Cluster Reply built a Foundation Layer / Unipol GenAI Stack combining an AI Data Layer (Azure AI Search and Vector DB indexing over 60,000 documents and 200,000+ metadata), a Core AI Layer orchestrating generative models and agents, and an AI Service Layer exposing AI capabilities to business applications, with shared guardrails for quality, ethics and compliance. On top of this, Cluster Reply developed a Virtual Information Assistant chatbot using RAG over 50,000+ UEBA documents and 200,000+ metadata; Sprint Reply built a network of AI agents using Azure OpenAI (GPT), LangChain and LangGraph for orchestration, Python, and UiPath for scalable execution; and Sprint Reply developed an AI Guardrail governance layer, based on the LoopMind asset, combining real-time LLM-as-a-judge controls, human-in-the-loop validation, and complete traceability of input/output/evaluations, deployable on-premises or in the cloud.
Reported business value
Reply reports accelerated time-to-value, with new applications released in 1-3 months thanks to reuse of common assets. The Virtual Information Assistant reduced back-office ticket load and cut time-to-resolution to a few seconds through semantic retrieval, while the AI Guardrail layer ensures real-time supervision and compliance, including alignment with the AI Act.
Sources
Open any source and check the claim yourself — that is the point of the register.
Other insurance entries in the register.
UNIQA SEE cuts health insurance claims processing times by 90% with Azure AI
UNIQA SEE's claims handlers faced fragmented documents, manual tasks, and heavy call-center reliance that slowed claims processing. Using Microsoft Azure AI alongside Microsoft Foundry, Azure Document Intelligence, and Azure OpenAI, UNIQA SEE built an end-to-end AI-driven medical referral solution that extracts, validates, and integrates referral letter data via APIs into the core claims system. The solution reduced claims processing time from 15-30 minutes to 2-3 minutes (an 85-90% reduction), lowered costs and call volumes, and freed staff for higher-value work. UNIQA SEE also introduced a self-service web and mobile app allowing customers to submit medical referral letters digitally. UNIQA SEE became the first insurer in Southeastern Europe to implement an AI-powered business process solution of this kind.
How Mapfre Insurance modernized fraud claims with Amazon EMR Serverless
Mapfre Insurance, the number one auto and home insurer in Massachusetts, modernized fraud detection by combining graph-based features from Neo4j with machine learning models deployed on AWS, using Amazon EMR Serverless, Apache Iceberg tables on Amazon S3, AWS Glue Data Catalog, AWS Lake Formation, and Amazon MWAA for orchestration. Fraud predictions integrate directly with Guidewire Claims via AWS Lambda, automatically creating claim activities showing the top model drivers for adjusters. The initiative, covering Massachusetts Auto insurance and later expanded to Home insurance, has delivered more than $5 million in Net Present Value, with detection accuracy improved 50-135 percent compared to baseline methods.
Efficiency meets data sovereignty: Lector automates document processing with AI
Lector, a platform for intelligent document processing used by more than 60 corporate customers including over 25 health insurers, migrated its productive cloud services from a major American cloud provider to OVHcloud's German data centre to meet GDPR and data-sovereignty requirements. Using OVHcloud Managed Kubernetes, S3-compatible Object Storage, and AI Training/AI Deploy/AI Endpoint services, Lector achieved over 80% time savings in document processing across more than 500 million pages processed to date, while reducing the operational burden of running Kafka and MongoDB themselves.
Generali France Rides the Wave of Microsoft 365 Copilot and Agentic AI with Microsoft
Generali France rolled out Microsoft 365 Copilot, Copilot Studio, and Azure OpenAI as part of its 'Boost 2027' strategic plan. 100% of employees have access to Copilot Chat and 3,700 use Microsoft 365 Copilot, with 70% of the workforce adopting it and generating an average of fifteen prompts per user per week. About fifty agents built with Copilot Studio address specialized cases including helpdesk operations. A 24/7 voice assistant resolves nearly 1.3 million calls (30% of requests) directly, with no human intervention. Generative AI also supports home insurance subscription, compliance beneficiary searches, and claims management, where 2.1 million operations were processed by RPA robots in 2024, including automated analysis of wall cracks during drought episodes (10% needing no human intervention) and recognition of more than 15 document types. Implementation was supported by Microsoft partner Avanade.
Was this helpful?
Your feedback helps us improve our use case database