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Development of AI-Powered Data Management and Underwriting Platform for Insurance Industry

intersog.com

Insurance

Technology

Business services

Current Challenges in Data Management and Underwriting

Relm Insurance faces inefficiencies in accessing and processing data across multiple databases, leading to time-consuming manual workflows, inconsistent underwriting decisions, and limited ability to extract actionable insights from unstructured data sources like documents and spreadsheets.

About the Client

Innovative insurance company specializing in coverage for technology-driven businesses

Strategic Goals for AI Platform Implementation

Automate data indexing and categorization across disparate systems
Enhance underwriting decision accuracy through AI-driven insights
Create unified access to structured and unstructured data sources
Implement scalable AI solution with future-proof architecture
Ensure compliance with industry security and data protection standards

Core Platform Capabilities

AI-powered semantic search engine with document indexing
Generative AI chat interface for complex data queries
Automated data structuring from unstructured documents
Contextual data enrichment using LLMs (ChatGPT integration)
Risk classification and financial information extraction
Source verification system for AI-generated outputs
Multi-tenancy security architecture with role-based access

Technology Stack Requirements

Microsoft Azure cloud platform

Azure AI Search

Azure Functions

Large Language Models (LLMs)

Microsoft Entra ID

SharePoint integration

System Integration Needs

Existing document management systems
Third-party AI tools (ChatGPT)
Security information and event management (SIEM) systems
Financial data APIs

Operational Requirements

Horizontal scalability for growing data volumes
Real-time search response performance
Enterprise-grade security with encryption at rest/in transit
Compliance with insurance industry regulations (e.g., GDPR, HIPAA)
High availability with 99.9% uptime SLA

Expected Business Outcomes

Implementation of this AI-powered platform is expected to reduce document processing time by 70%, increase underwriting decision accuracy through enriched data insights, improve analyst productivity with automated report generation, and establish a scalable foundation for future AI capabilities while maintaining strict regulatory compliance.