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AI-Powered Customer Service Assistant for Financial Services Platform
  1. case
  2. AI-Powered Customer Service Assistant for Financial Services Platform

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AI-Powered Customer Service Assistant for Financial Services Platform

firstlinesoftware.com
Financial services
Information technology

Challenges in Customer Engagement and Support Scalability

Users struggle with complex information retrieval via outdated search tools, inefficient query resolution diminishes satisfaction, lack of real-time personalized interactions limits revenue growth, and absence of scalable online support increases operational costs.

About the Client

A financial services provider offering investment products like ETFs and mutual funds through a digital platform serving individual and institutional clients globally.

Strategic Goals for Platform Enhancement

  • Implement AI-driven search functionality for faster, accurate product information retrieval
  • Deliver scalable, real-time customer support to reduce operational costs
  • Enhance user satisfaction through personalized, conversational interactions
  • Establish foundation for future multilingual and dynamic data capabilities

Core System Capabilities

  • Natural language interface with context retention for multi-turn conversations
  • Vectorized product search for ETFs/mutual funds by name, features, or descriptions
  • Integration with Optimizely CMS for real-time content synchronization
  • Feedback loops for response quality ratings and escalation to human agents
  • Conversational tone with structured response formatting for clarity

Technology Stack Requirements

Azure Functions
LangSmith
LangFuse
Generative AI models

System Integration Needs

  • Optimizely (EpiServer) CMS
  • User authentication systems
  • Analytics platforms

Operational and Security Standards

  • Horizontal scalability for fluctuating query volumes
  • Enterprise-grade data security and compliance (GDPR, SOC2)
  • 99.9% system availability with failover mechanisms
  • Real-time response latency under 2 seconds
  • Content filtering and hallucination mitigation techniques

Anticipated Business Outcomes

Reduction in customer information retrieval time by 60-70%, 40% decrease in support operational costs through automation, 25% increase in product discovery-driven conversions, and ability to scale support capacity linearly with customer growth without proportional staffing increases.

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