{"version":"1.0","provider_name":"","provider_url":"https:\/\/fleurendoua.com","author_name":"admin8805","author_url":"https:\/\/fleurendoua.com\/index.php\/author\/admin8805\/","title":"AI Customer Support Agent -","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"reJS0qNtvW\"><a href=\"https:\/\/fleurendoua.com\/index.php\/ai-customer-support-agent\/\">AI Customer Support Agent<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/fleurendoua.com\/index.php\/ai-customer-support-agent\/embed\/#?secret=reJS0qNtvW\" width=\"600\" height=\"338\" title=\"\u00ab\u00a0AI Customer Support Agent\u00a0\u00bb &#8212; \" data-secret=\"reJS0qNtvW\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script>\n\/*! This file is auto-generated *\/\n!function(d,l){\"use strict\";l.querySelector&&d.addEventListener&&\"undefined\"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!\/[^a-zA-Z0-9]\/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),o=l.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),c=new RegExp(\"^https?:$\",\"i\"),i=0;i<o.length;i++)o[i].style.display=\"none\";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute(\"style\"),\"height\"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):\"link\"===t.message&&(r=new URL(s.getAttribute(\"src\")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener(\"message\",d.wp.receiveEmbedMessage,!1),l.addEventListener(\"DOMContentLoaded\",function(){for(var e,t,s=l.querySelectorAll(\"iframe.wp-embedded-content\"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute(\"data-secret\"))||(t=Math.random().toString(36).substring(2,12),e.src+=\"#?secret=\"+t,e.setAttribute(\"data-secret\",t)),e.contentWindow.postMessage({message:\"ready\",secret:t},\"*\")},!1)))}(window,document);\n\/\/# sourceURL=https:\/\/fleurendoua.com\/wp-includes\/js\/wp-embed.min.js\n<\/script>\n","description":"AI Customer Support Agent: RAG-Powered Automation The context The project was developed to modernize customer service for a travel-tech environment (Dayuse-like model). Traditional support bots often fail by providing generic answers or \u00ab\u00a0hallucinating\u00a0\u00bb facts. I built a custom Retrieval-Augmented Generation (RAG) system using n8n to bridge the gap between static FAQ documentation and dynamic customer interactions. The purpose The goal was to create a reliable, low-latency automated agent capable of: Factual Accuracy: Providing answers based strictly on a private CSV-based knowledge base. Intelligent Escalation: Detecting negative sentiment or low-confidence responses to automatically create tickets in Zendesk. Operational Efficiency: reducing manual agent workload by resolving common queries (e.g., \u00ab\u00a0What is Dayuse?\u00a0\u00bb) without human intervention. The results Zero Hallucination Rate: Successfully restricted the AI to official documentation, ensuring 100% brand-safe responses. Seamless Ticketing: Automated the creation of detailed Zendesk tickets, including full conversation logs and sentiment analysis for human agents. Scalability: Built a flexible architecture that can update its knowledge base in real-time simply by modifying a Google Drive file. Cost Optimization: Transformed an inefficient 91-call process into a streamlined 1-call execution. My role\u00a0 As the Automation specialist, I was responsible for the end-to-end development of the workflow: System Architecture: Designed the multi-branch logic in n8n, connecting Webhooks, AI Agents, and external APIs (Zendesk, Google Drive). Data Engineering: Wrote custom JavaScript to consolidate 90+ rows of FAQ data into a single AI-ready context, optimizing token usage and reducing API costs by 98%. AI Orchestration: Configured LangChain agents with specific \u00ab\u00a0guardrail\u00a0\u00bb prompts to prevent misinformation. Debugging: Resolved complex JSON issues and asynchronous data persistence problems Core Logic Orchestration: n8n LLMs: OpenAI (GPT-4o \/ GPT-5 Nano) Data Sources: Google Drive (CSV FAQ), Google Sheets Ticketing\/CRM: Zendesk API Workflow Ingestion: Receives customer queries and metadata via Webhook.\u00a0 Contextualization: Fetches and transforms FAQ data from Google Drive into a searchable knowledge base.\u00a0 Processing: Sentiment Analysis: Categorizes user emotion (Positive\/Neutral\/Negative).RAG Agent: Generates answers based strictly on the FAQ context. Confidence Scoring: Programmatically evaluates the AI&rsquo;s answer quality.\u00a0 Action: Success: Delivers the verified answer back to the chat interface. Escalation: If confidence is low or sentiment is negative, creates a Zendesk Ticket with full conversation logs. PHONE +33667368654 EMAIL allua.ndoua@sciencespo.fr\u00a0 FOLLOW ME Linkedin","thumbnail_url":"http:\/\/fleurendoua.com\/wp-content\/uploads\/2026\/04\/af2fc5_e384dc57d5d54e4e89a7ecd1de481a54mv2.png"}