CASE STUDY

Next-Generation RAG + GenAI Chatbot
for Live Customer Engagement

AI
Automotive

Project Highlights

Scope

  • Developed an AI-powered Live Person Chatbot using RAG architecture and Generative AI (GenAI) to enhance real-time customer interactions.
  • Connected enterprise knowledge bases, policy documents, and historical data to support accurate, context-aware responses.
  • Enabled human-like conversational capabilities with personalised, empathetic, and compliant messaging.
  • Designed for seamless integration into existing customer service environments for multi-channel support.

Challenges Overcome

Reliable information retrieval: The system now accesses trusted knowledge sources in real time to prevent inconsistencies and misinformation.

Human-like communication: Responses that previously required agent intervention are now generated with clarity, empathy, and contextual accuracy.

Reduced agent dependency: Repetitive inquiries that once consumed significant agent time are now handled autonomously.

Scalable service delivery: Customer interactions can now be supported across multiple touchpoints without expanding support teams.

Business Impact

The chatbot significantly improves customer engagement efficiency while ensuring consistent, compliant, and accurate communication.

  • 50% reduction in repetitive query workload for support teams.
  • Instant responses providing faster customer resolution times.
  • Consistency across 100% of automated replies aligned with communication standards.
  • Scalable deployment across multiple customer service channels.

The Problem

Customer support teams faced increasing pressure to deliver fast, accurate responses across growing volumes of inquiries.

  • High workload due to repetitive informational queries.
  • Difficulty maintaining consistency and compliance across all interactions.
  • Limited ability to scale support without expanding operational costs.
  • Delays in accessing up-to-date information from internal systems during live conversations.

The Solution

BGTS implemented a sophisticated RAG-enabled chatbot powered by GenAI, designed for real-time, human-like support across customer channels.

RAG-based information retrieval: Fetches precise, up-to-date knowledge from enterprise sources during live chat sessions.

GenAI-driven conversational responses: Generates context-aware replies that mirror human tone, clarity, and empathy.

Seamless escalation flow: Automatically routes complex or sensitive cases to human agents with full context attached.

Continuous learning: Improves accuracy, intent understanding, and response style over time through interaction data.

Team & Technology

Technology Stack

Core & Orchestration

  • LangGraph/AutoGen (agent flows + guardrails)
  • Python

Models

  • GPT-class LLMs via Azure OpenAI/OpenAI; lightweight domain classifiers; structured extraction

RAG/Knowledge

  • pgvector (Postgres) or Weaviate; LlamaIndex/Haystack for retrieval

Services & Integration

  • FastAPI microservices; Microsoft Graph (M365/Exchange) for email I/O; REST/webhooks to claims/CRM + garage systems

Messaging/Workflow

  • RabbitMQ or Azure Service Bus; Temporal/Durable Functions (optional)

Data & Storage

  • Postgres (operational), object storage for artefacts

MLOps & Observability

  • MLflow (registry)
  • OpenTelemetry → ELK/OpenSearch
  • Prometheus + Grafana

Security & Compliance

  • Vault/Key Vault
  • RBAC
  • PII redaction
  • immutable audit logs

Infra & DevEx

  • Docker + Kubernetes (AKS/EKS) or serverless; Terraform; CI/CD via GitHub Actions/Azure DevOps

Team Composition

1 Tech Lead / Solution Architect

1 Product & Delivery Lead

1 Full-stack/API Engineer

1 Integration & MLOps Engineer

1 AI/Orchestration Engineer

The Outcome

Enhanced customer experience: Faster, more accurate, and human-like responses during live interactions.

Reduced support workload: Automated handling of high-volume informational queries.

Consistent communication: AI-generated responses fully aligned with policy and compliance guidelines.

Scalable deployment: Unified orchestration enabling expansion across multiple channels and services.