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AI-Powered Contract Standardization and Data Extraction System
  1. case
  2. AI-Powered Contract Standardization and Data Extraction System

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AI-Powered Contract Standardization and Data Extraction System

spyro-soft.com
Insurance
Financial services

Manual Data Processing Challenges

Underwriters spend excessive time manually transferring data from broker documents (4-50 pages) into insurance offers. Inconsistent field naming conventions, varying document structures, and lack of standardized templates lead to inefficiencies, errors, and delayed client responses. Brokers use non-standard clauses and formats, requiring additional time for validation and standardization.

About the Client

Leading insurance provider in Central and Eastern Europe offering property, life, health, and motor insurance for individuals and corporations

Automation and Standardization Goals

  • Automate extraction of critical data from broker documents
  • Standardize contract templates across all regions and products
  • Reduce manual data entry time by 80-90%
  • Improve first-response time to clients
  • Increase contract signing rates through faster processing

Core System Capabilities

  • AI-based data extraction using LLMs with custom parsers
  • Clause validation and standardization engine
  • Unified contract template generation
  • Interactive review interface for underwriters
  • Centralized clause database with role-based access

Technology Stack

Azure OpenAI (GPT4o)
LangChain
Chroma DB
Azure DevOps
Vector database

System Integrations

  • Microsoft Graph API for email connectivity
  • Azure CI/CD pipelines
  • Document storage systems

Non-Functional Requirements

  • GDPR-compliant data security
  • High-availability cloud architecture
  • Scalable document processing capacity
  • Low-latency AI inference

Business Impact Projections

Processing speed increased 2-3x with underwriter verification time reduced to minutes. Standardized templates and centralized clause management improve compliance and reduce errors. Faster response times expected to increase signed contracts by 50% while maintaining underwriting team size.

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