Overview

Our client, a global lifestyle brand, wanted to enhance customer engagement and support by deploying a centralized AI chatbot across multiple touchpoints. The solution needed to combine WhatsApp chat triggered via QR codes on products, a website chatbot, and integration with their CRM for automated routing. Bacancy’s LLM and AI developers built a production-ready platform leveraging LLMs for multi-intent understanding, personalized recommendations, and bilingual interactions, providing customers with contextual content, support, and inspiration while enabling scalable personalization and analytics.

Technical Stack

  • OpenAI GPT
  • LangChain
  • Twilio
  • React.js
  • Node.js
  • CleverTap
  • MongoDB
  • Zapier
  • n8n
  • GitHub Actions

    • Industry

    Retail

  • region

    • Region

    Australia

  • project-size

    • Project Size

    Non-Disclosable

Highlights

Built a centralized LLM-powered AI chatbot operating across WhatsApp QR codes and website.

Integrated with CRM for automated routing of complaints, queries, and follow-ups.

Personalized multi-intent interactions: content inspiration, FAQs, complaints, and customer queries.

Bilingual support: Arabic & English interactions.

Challenges & Solutions

The client wanted a multi-channel chatbot that could maintain consistent context and personalization across platforms.

  • Solution: Our LLM development company implemented a robust core engine to unify conversations across WhatsApp and the website. The engine ensures contextual continuity, remembers previous interactions, and delivers personalized responses for each user.

The client faced the problem of automating product-specific content delivery based on QR scans.

  • Solution: We connected QR codes to LLM-driven WhatsApp chatbot workflows. When scanned, the system dynamically fetches product or category-specific content and recommendations, providing instant, relevant responses to user queries.

The client wanted to manage bilingual content efficiently for global users.

  • Solution: Our team fine-tuned LLMs to understand both Arabic and English. The chatbot can accurately respond in either language, maintaining consistent tone and user experience across conversations.

The client needed customer interactions synced with their CRM for analytics and follow-ups.

  • Solution: We developed automated CRM integration that logs every conversation, triggers follow-up actions, and generates detailed dashboards. This allows the client to track engagement, monitor performance, and improve customer support efficiency.

Core Features

  • QR-triggered WhatsApp chatbot for product-specific content delivery and customer support
  • LLM-powered website chatbot for personalized recommendations and conversational assistance
  • Automated CRM integration for efficient query, complaint, and interaction management
  • Integrated content library for context-aware inspiration and FAQ delivery
  • no.-of-resources

    • No. of Developers

    06

  • time-frame

    • Time Frame

    May 2025 - August 2025

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