SmartSupport AI - Multilingual Support Agent

Project CategoryAI/ML Solutions

Publication Date2024-12-15

SmartSupport AI - Multilingual Support Agent

01. The Challenge

A global retail giant was overwhelmed by a surge in support tickets across multiple languages. Their human agents were spending significant time on repetitive Level 1 queries, leading to high burnout and slow response times for complex issues. They needed an AI solution that was more than just a chatbot—a deeply integrated agent capable of understanding nuances, accessing customer history safely, and resolving issues autonomously in real-time.

Technology Stack

OpenAI GPT-4oLangChainPinecone (Vector DB)Python (FastAPI)ReactTerraformAzure OpenAI Service

02. Our Solution

We developed 'SmartSupport AI', an advanced virtual assistant powered by Large Language Models (LLMs). We utilized RAG (Retrieval-Augmented Generation) to ground the AI in the client's specific knowledge base and CRM data. The system features a custom-built prompt engineering layer to ensure the brand's tone of voice is maintained. We integrated it directly with their existing Zendesk and Salesforce instances, allowing the AI to perform actions like processing returns and updating shipping addresses through secure API calls.

Context-Aware RAG Architecture: Grounds AI responses in company documentation to eliminate halluncinations.

Unified Multilingual Engine: Seamlessly supports 15+ languages without requiring separate translation layers.

Action-Oriented API Bridge: Allows the AI to autonomously resolve tickets by interacting with CRM and ERP systems.

Sentiment Analysis Guardrails: Automatically escalates frustrated customers to human senior managers in real-time.

Brand Voice Profiling: Custom-tuned LLM parameters to match the client's professional and empathetic tone.

Automated Knowledge Mining: Learns from successful human agent interactions to constantly improve its accuracy.

03. The Process

Phase 1: Knowledge Audit & Data Cleaning to prepare the foundation for the Vector Database.

Phase 2: RAG Pipeline Development and Vectorization of company policies and product manuals.

Phase 3: Secure API Integration with Salesforce and Zendesk for transactional capabilities.

Phase 4: Prompt Engineering & Fine-tuning to establish the specific brand persona and tone.

Phase 5: Parallel Running & Human-in-the-loop testing to verify accuracy and safety guardrails.

Phase 6: Multi-Country Deployment with continuous performance monitoring and feedback loops.

04. Project Outcome

The implementation successfully transformed the client's operations, setting a new benchmark for efficiency and reliability in their sector. By combining cutting-edge technology with a user-centric design approach, we delivered a platform that scales with their ambition.

High Level 1 Resolution AI now handles majority of all incoming queries autonomously.

Fast Response Times Drastically reduced Wait Time to near-instant responses.

Reduced CSAT Friction Human agents now focus exclusively on high-value, complex cases.

Lower Costs Achieved significant reduction in support-related operational expenditure.

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