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AI-Driven SaaS Platform for Insurance

Transforming life insurance accessibility with a multi-carrier digital platform that leverages behavioral AI to bridge the 100-million-household coverage gap.

Client

An emerging US insurtech innovator focused on data-driven customer outreach and ROI.

Problem Statement

Legacy distribution models created barriers to entry, leaving millions of US households uninsured due to high acquisition costs and poor digital access.

Industry

Financial Services

High-Tech

Solution

Intelligent Enterprise

Digital Experience

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Quick Summary

  • Engineered a comprehensive multi-carrier SaaS platform that integrates lead generation, automates underwriting, and policy administration into a single secure ecosystem.
  • Developed a patent-pending AI/ML engine to identify "warm leads" and a graph-database-driven journey engine to deliver personalized, high-performance customer experiences.
  • Delivered a 65% reduction in customer acquisition costs and a 36% increase in ROI, successfully tapping into 45% of the previously unserved US market.

Client Profile

The client is an emerging insurtech company, driving innovation and disruption in the United States insurance industry. The client focuses on solutions that track customer data, transform numbers into tangible insights, and improve insurers’ outreach and ROI.
 

Challenges: Breaking Legacy Barriers

  • Market Inaccessibility: Over 100 million US households remained uninsured or underinsured due to a lack of digital awareness and transaction ease.
  • Prohibitive Costs: Traditional insurance models suffered from high acquisition costs and a heavy reliance on expensive manual intermediaries.
  • Rigid Infrastructure: Legacy systems couldn't adapt to mortality fluctuations or the rapid pace of digital-native competitors.

QBurst Solution: Intelligent End-to-End Automation

QBurst built a scalable, microservices-based SaaS platform that covers the entire insurance lifecycle—from lead nurturing to claim settlement. The solution utilizes Azure Kubernetes Service (AKS) for orchestration and Neo4j Graph DB to power complex user journeys.

  • Predictive Lead Scoring: A patent-pending ML engine analyzes data from financial institutions and partners to score and prioritize the most viable prospects.
  • Behavioral Marketing & Nurturing: Automated workflows via Hangfire and RabbitMQ deliver personalized digital content to convert leads across various channels.
  • AI-Powered Underwriting: A rule-based engine triggers health and demographic questionnaires in real-time, providing instant offers based on customer inputs.
  • Unified Administration: A central module manages active policies, automated agent commissions, and claim fulfillments seamlessly.

Technical Highlights

  • Graph-Based Journey Engine: Utilizes Neo4j and plug-and-play widgets to configure high-performance, personalized user journeys for affiliates.
  • Microservices Architecture: Ensures parallel integration and independent scaling of niche applications (e.g., life, annuity, and medicare) without blocking dependencies.
  • Advanced Analytics: Integrated Power BI dashboards for real-time visualization of lead KPIs and marketing spend effectiveness.
  • Enterprise Security: Meets OWASP standards and is architected for SOC2 compliance using Azure Front Door and secure VPN gateways.
     

Impact

  • 36% Increase in ROI: Driven by optimized marketing spend and precision targeting.
  • 65% Reduction in Acquisition Costs: AI-driven lead scoring significantly lowered the cost of finding and converting customers.
  • Market Penetration: Successfully reached a large segment of the previously unserved US insurance market.
  • 34% Higher Conversion: Personalized customer journeys and electronic form fulfillment led to faster policy activations.
     

Client

The Challenge

QBurst Solution

Technical Highlights

Impact

Recognized for Growth. Trusted for Impact.

Deloitte Technology Fast 50 India, Winner 2024

Deloitte Fast 50 India, Winner 2024

Dun & Bradstreet

Leading Mid-Corporates of India, 2024

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Major Contender, QE Specialist Services


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