Multi-Agent Personalized Insurance Policy Recommendation for Healthcare

The challenge

A healthcare insurance organization aimed to improve customer experience by implementing an AI-powered advisory platform capable of recommending personalized insurance policies based on individual health, lifestyle, and financial needs. The objective was to simplify policy selection, improve transparency, and help customers choose plans best suited to their medical and budgetary requirements. The solution was designed to analyze customer profiles holistically, simplify complex insurance terminology, and provide intelligent recommendations that balance coverage, affordability, and long-term healthcare needs.

Key challenges

• Customers struggling to identify healthcare plans suitable for their specific needs and budgets
• Complex insurance terminology causing confusion and reduced customer confidence
• Difficulty comparing multiple policy options effectively
• Lack of personalized guidance during insurance selection processes
• Limited customer engagement after policy purchase affecting renewals and retention

Technology used

• Programming Language: Python
• Framework: LangGraph for multi-agent workflow orchestration
• AI Capabilities: Personalized recommendation engine, customer profiling, and intelligent policy matching

What we built

• Customer Profile Analysis Agent: Collects and analyzes demographic, lifestyle, medical history, and financial information to build customer profiles
• Benefit Explanation Agent: Converts technical insurance terminology into easy-to-understand summaries for customers
• Policy Matching Agent: Evaluates and scores available healthcare plans based on customer suitability and coverage requirements
• Feedback Collection Agent: Captures customer feedback to improve recommendation accuracy and scoring models
• Policy Management Agent: Assists customers with post-purchase actions such as claims, renewals, and policy upgrades

Objectives

• Provide personalized healthcare insurance recommendations based on customer profiles
• Simplify complex insurance policy language for better understanding
• Improve customer trust through transparent and explainable recommendations
• Match insurance plans based on health risks, lifestyle, and financial preferences
• Enhance customer engagement through intelligent post-purchase support
• Improve policy selection efficiency while reducing manual advisory efforts

Outcomes

• Highly personalized insurance recommendations based on complete customer profiling
• Improved transparency through simplified policy explanations and better customer understanding
• Optimized plan selection balancing healthcare coverage needs and affordability
• Enhanced customer satisfaction through tailored recommendations and advisory support
• Improved retention through proactive reminders for renewals and policy management
• Scalable AI-driven advisory system for healthcare insurance recommendation and customer engagement