ABHISHEK UPADHYAY 
Projects

June 1, 2025

AI-Powered Virtual Relationship Manager

Enterprise Conversational AI & Real-Time Voice Banking Platform | Senior Frontend Developer

Overview

A mission-critical conversational AI and real-time voice banking platform for an enterprise banking institution, serving 4.5M+ active users. The platform pairs a real-time voice and avatar layer with a multilingual, RAG-powered conversational engine to deliver assisted banking at scale.

Key Features

  • Mission-Critical Frontend Architecture: Spearheaded frontend client architecture for an AI-powered conversational portal serving 4.5M+ active users, prioritizing low-latency audio streaming, high availability, and fluid UX.
  • Real-Time Voice & Avatar Layer: Architected a real-time voice and audio layer using WebRTC, Azure Speech/Cognitive Services, Azure Avatar, and Bot Framework Web Chat with custom neural voice support.
  • Latency & Completion Rate Gains: Slashed interaction latency by 20% and improved end-to-end conversation completion rates by 12–18% through predictive UI state machines and buffered message streaming pipelines.
  • Concurrency-Safe State Architecture: Engineered a query queuing mechanism and Redux Toolkit state architecture to prevent race conditions across concurrent AI responses, WebSocket/SSE streams, and voice interactions.
  • Localized Multilingual Support: Implemented multilingual (Hindi–English) support with SSML processing for Indian numbering formats (lakh/crore), alongside cost-conscious auto-teardown controls for idle sessions.
  • Enterprise-Grade Security: Enforced AES encryption, CSRF/XSS protection, secure token lifecycle management, and strict HTTPS transport protocols.

Technologies Used

  • React.js + Vite + TypeScript: For a fast, type-safe front-end build and dev pipeline.
  • Tailwind CSS: For a consistent, themeable UI across voice and chat surfaces.
  • Redux Toolkit: For concurrency-safe state management across call, chat, and session state.
  • WebRTC: For real-time bidirectional voice communication between the customer and the assistant.
  • Azure Speech SDK + Azure Avatar: For neural voice synthesis, speech recognition, and avatar rendering.
  • Bot Framework + Direct Line API: For connecting the chat widget to the conversational backend.
  • Adaptive Cards: For structured, interactive responses inside the chat interface.
  • RAG: For grounding conversational responses in the institution's own knowledge base.
  • WebSockets: For real-time, bidirectional streaming of AI responses and session events.
  • AES Encryption: For encrypting sensitive data in transit and at rest.
  • Azure DevOps + Git: For CI/CD and version control across the frontend codebase.

Outcome

The platform now handles assisted banking conversations for 4.5M+ active users at an enterprise banking institution, reducing dependency on call-center volume while keeping voice and chat interactions secure, fast, and resilient under real-world network conditions.