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Conversational UX for GenAI-Enabled Support Systems

Overview

A leading global financial services provider, operating across banking, insurance, and wealth management, faced mounting pressure to modernize its customer support systems. Despite investments in digital channels and AI chatbots, the organization struggled to deliver a truly conversational UX that felt intuitive, real-time, and context-aware.

Client Background and Challenges

The client’s support ecosystem was fragmented across multiple platforms — web, mobile, IVR, and email — with inconsistent user experiences and limited automation. Customers frequently encountered rigid decision trees, irrelevant responses, and long wait times. Internally, support agents lacked real-time assistance, leading to high handling times and low first-contact resolution.

DeltaDot AI’s Approach

DeltaDot AI proposed a Conversational UX Transformation Framework built on GenAI and LLMs, designed to unify customer support across channels, augment human agents, and deliver personalized, compliant, and intuitive experiences.

Conversational Intelligence Layer

GenAI-powered virtual assistants capable of understanding natural language, context and sentiment, with Retrieval-Augmented Generation (RAG) for accurate, real-time responses.

Agent Augmentation Layer

An Agent Copilot interface providing real-time suggestions, summaries, and compliance prompts, with contextual knowledge retrieval from enterprise repositories.

UX Orchestration Layer

A unified conversational design system for consistent experiences across web, mobile, and voice, with accessibility and inclusivity features for diverse user groups.

Solution Highlights

  • AI-Optimized Infrastructure: core workloads migrated to a hybrid cloud setup with GPU-enabled clusters for high-performance model training.
  • Elastic Scalability: auto-scaling of compute resources based on workload intensity, reducing idle costs by 40%.
  • Real-Time Insights: real-time inference engines for fraud detection and portfolio risk analysis, reducing latency by 60%.
  • Governance Automation: policy-as-code frameworks to ensure continuous compliance across environments.

Scalable Governance and Risk Management

  • A collaborative governance framework for faster decision-making and adaptive risk control.
  • Automated policy enforcement and real-time auditing to strengthen compliance and security.
  • An enterprise-wide knowledge-sharing platform to drive continuous learning and upskilling.

Conclusion

By combining the power of large language models with human-centric design, the client was able to deliver intuitive, intelligent, and compliant support experiences across channels — transforming customer engagement from transactional interactions to meaningful conversations.

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